CircleCI
官方Enable AI Agents to fix build failures from CircleCI.
CircleCI MCP Server
Model Context Protocol (MCP) is a new, standardized protocol for managing context between large language models (LLMs) and external systems. In this repository, we provide an MCP Server for CircleCI.
Use Cursor, Windsurf, Copilot, Claude, or any MCP-compatible client to interact with CircleCI using natural language — without leaving your IDE.
Tools
| Tool | Description |
|---|---|
analyze_diff | Analyze git diffs against cursor rules for violations |
config_helper | Validate and get guidance for your CircleCI configuration |
create_prompt_template | Generate structured prompt templates for AI applications |
download_usage_api_data | Download usage data from the CircleCI Usage API |
find_flaky_tests | Identify flaky tests by analyzing test execution history |
find_underused_resource_classes | Find jobs with underused compute resources |
get_build_failure_logs | Retrieve detailed failure logs from CircleCI builds |
get_job_test_results | Retrieve test metadata and results for CircleCI jobs |
get_latest_pipeline_status | Get the status of the latest pipeline for a branch |
list_artifacts | List artifacts produced by a CircleCI job |
list_component_versions | List all versions for a CircleCI component |
list_followed_projects | List all CircleCI projects you're following |
recommend_prompt_template_tests | Generate test cases for prompt templates |
rerun_workflow | Rerun a workflow from start or from the failed job |
run_evaluation_tests | Run evaluation tests on a CircleCI pipeline |
run_pipeline | Trigger a pipeline to run |
run_rollback_pipeline | Trigger a rollback for a project |
Installation
Cursor
Prerequisites:
- CircleCI Personal API token (learn more)
- NPX: Node.js >= v18 and pnpm
- Docker: Docker
Using NPX in a local MCP Server
Add the following to your Cursor MCP config:
{
"mcpServers": {
"circleci-mcp-server": {
"command": "npx",
"args": ["-y", "@circleci/mcp-server-circleci@latest"],
"env": {
"CIRCLECI_TOKEN": "your-circleci-token",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
}
}
}
}
CIRCLECI_BASE_URLis optional — required for on-prem customers only.MAX_MCP_OUTPUT_LENGTHis optional — maximum output length for MCP responses (default: 50000).
Using Docker in a local MCP Server
Add the following to your Cursor MCP config:
{
"mcpServers": {
"circleci-mcp-server": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"CIRCLECI_TOKEN",
"-e",
"CIRCLECI_BASE_URL",
"-e",
"MAX_MCP_OUTPUT_LENGTH",
"circleci/mcp-server-circleci"
],
"env": {
"CIRCLECI_TOKEN": "your-circleci-token",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
}
}
}
}
Using a Self-Managed Remote MCP Server
Add the following to your Cursor MCP config:
{
"inputs": [
{
"type": "promptString",
"id": "circleci-token",
"description": "CircleCI API Token",
"password": true
}
],
"servers": {
"circleci-mcp-server-remote": {
"url": "http://your-circleci-remote-mcp-server-endpoint:8000/mcp"
}
}
}
VS Code
Prerequisites:
- CircleCI Personal API token (learn more)
- NPX: Node.js >= v18 and pnpm
- Docker: Docker
Using NPX in a local MCP Server
Add the following to .vscode/mcp.json in your project:
{
"inputs": [
{
"type": "promptString",
"id": "circleci-token",
"description": "CircleCI API Token",
"password": true
},
{
"type": "promptString",
"id": "circleci-base-url",
"description": "CircleCI Base URL",
"default": "https://circleci.com"
}
],
"servers": {
"circleci-mcp-server": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@circleci/mcp-server-circleci@latest"],
"env": {
"CIRCLECI_TOKEN": "${input:circleci-token}",
"CIRCLECI_BASE_URL": "${input:circleci-base-url}"
}
}
}
}
💡 Inputs are prompted on first server start, then stored securely by VS Code.
Using Docker in a local MCP Server
Add the following to .vscode/mcp.json in your project:
{
"inputs": [
{
"type": "promptString",
"id": "circleci-token",
"description": "CircleCI API Token",
"password": true
},
{
"type": "promptString",
"id": "circleci-base-url",
"description": "CircleCI Base URL",
"default": "https://circleci.com"
}
],
"servers": {
"circleci-mcp-server": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"CIRCLECI_TOKEN",
"-e",
"CIRCLECI_BASE_URL",
"circleci/mcp-server-circleci"
],
"env": {
"CIRCLECI_TOKEN": "${input:circleci-token}",
"CIRCLECI_BASE_URL": "${input:circleci-base-url}"
}
}
}
}
Using a Self-Managed Remote MCP Server
Add the following to .vscode/mcp.json in your project:
{
"servers": {
"circleci-mcp-server-remote": {
"type": "sse",
"url": "http://your-circleci-remote-mcp-server-endpoint:8000/mcp"
}
}
}
Claude Desktop
Prerequisites:
- CircleCI Personal API token (learn more)
- NPX: Node.js >= v18 and pnpm
- Docker: Docker
Using NPX in a local MCP Server
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"circleci-mcp-server": {
"command": "npx",
"args": ["-y", "@circleci/mcp-server-circleci@latest"],
"env": {
"CIRCLECI_TOKEN": "your-circleci-token",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
}
}
}
}
Using Docker in a local MCP Server
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"circleci-mcp-server": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"CIRCLECI_TOKEN",
"-e",
"CIRCLECI_BASE_URL",
"-e",
"MAX_MCP_OUTPUT_LENGTH",
"circleci/mcp-server-circleci"
],
"env": {
"CIRCLECI_TOKEN": "your-circleci-token",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
}
}
}
}
Using a Self-Managed Remote MCP Server
Create a wrapper script (e.g. circleci-remote-mcp.sh):
#!/bin/bash
export CIRCLECI_TOKEN="your-circleci-token"
npx mcp-remote http://your-circleci-remote-mcp-server-endpoint:8000/mcp --allow-http
Make it executable:
chmod +x circleci-remote-mcp.sh
Then add the following to your claude_desktop_config.json:
{
"mcpServers": {
"circleci-remote-mcp-server": {
"command": "/full/path/to/circleci-remote-mcp.sh"
}
}
}
To find or create your config file, open Claude Desktop settings, click Developer in the left sidebar, then click Edit Config. The config file is located at:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
For more information: https://modelcontextprotocol.io/quickstart/user
Claude Code
Prerequisites:
- CircleCI Personal API token (learn more)
- NPX: Node.js >= v18 and pnpm
- Docker: Docker
Using NPX in a local MCP Server
claude mcp add circleci-mcp-server -e CIRCLECI_TOKEN=your-circleci-token -- npx -y @circleci/mcp-server-circleci@latest
Using Docker in a local MCP Server
claude mcp add circleci-mcp-server -e CIRCLECI_TOKEN=your-circleci-token -e CIRCLECI_BASE_URL=https://circleci.com -- docker run --rm -i -e CIRCLECI_TOKEN -e CIRCLECI_BASE_URL circleci/mcp-server-circleci
Using a Self-Managed Remote MCP Server
claude mcp add circleci-mcp-server -e CIRCLECI_TOKEN=your-circleci-token -- npx mcp-remote http://your-circleci-remote-mcp-server-endpoint:8000/mcp --allow-http
For more information: https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/tutorials#set-up-model-context-protocol-mcp
Windsurf
Prerequisites:
- CircleCI Personal API token (learn more)
- NPX: Node.js >= v18 and pnpm
- Docker: Docker
Using NPX in a local MCP Server
Add the following to your Windsurf mcp_config.json:
{
"mcpServers": {
"circleci-mcp-server": {
"command": "npx",
"args": ["-y", "@circleci/mcp-server-circleci@latest"],
"env": {
"CIRCLECI_TOKEN": "your-circleci-token",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
}
}
}
}
Using Docker in a local MCP Server
Add the following to your Windsurf mcp_config.json:
{
"mcpServers": {
"circleci-mcp-server": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"CIRCLECI_TOKEN",
"-e",
"CIRCLECI_BASE_URL",
"-e",
"MAX_MCP_OUTPUT_LENGTH",
"circleci/mcp-server-circleci"
],
"env": {
"CIRCLECI_TOKEN": "your-circleci-token",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
}
}
}
}
Using a Self-Managed Remote MCP Server
Add the following to your Windsurf mcp_config.json:
{
"mcpServers": {
"circleci": {
"command": "npx",
"args": [
"mcp-remote",
"http://your-circleci-remote-mcp-server-endpoint:8000/mcp",
"--allow-http"
],
"disabled": false,
"alwaysAllow": []
}
}
}
For more information: https://docs.windsurf.com/windsurf/mcp
Amazon Q Developer CLI
Prerequisites:
- CircleCI Personal API token (learn more)
- NPX: Node.js >= v18 and pnpm
MCP client configuration in Amazon Q Developer is stored in JSON format in a file named mcp.json. Two levels of configuration are supported:
- Global:
~/.aws/amazonq/mcp.json— applies to all workspaces - Workspace:
.amazonq/mcp.json— specific to the current workspace
If both files exist, their contents are merged. In case of conflict, the workspace config takes precedence.
Using NPX in a local MCP Server
Edit ~/.aws/amazonq/mcp.json or create .amazonq/mcp.json with the following:
{
"mcpServers": {
"circleci-local": {
"command": "npx",
"args": [
"-y",
"@circleci/mcp-server-circleci@latest"
],
"env": {
"CIRCLECI_TOKEN": "YOUR_CIRCLECI_TOKEN",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
},
"timeout": 60000
}
}
}
Using a Self-Managed Remote MCP Server
Create a wrapper script (e.g. circleci-remote-mcp.sh):
#!/bin/bash
export CIRCLECI_TOKEN="your-circleci-token"
npx mcp-remote http://your-circleci-remote-mcp-server-endpoint:8000/mcp --allow-http
Make it executable and add it:
chmod +x circleci-remote-mcp.sh
q mcp add --name circleci --command "/full/path/to/circleci-remote-mcp.sh"
Amazon Q Developer in the IDE
Prerequisites:
- CircleCI Personal API token (learn more)
- NPX: Node.js >= v18 and pnpm
Using NPX in a local MCP Server
Edit ~/.aws/amazonq/mcp.json or create .amazonq/mcp.json with the following:
{
"mcpServers": {
"circleci-local": {
"command": "npx",
"args": [
"-y",
"@circleci/mcp-server-circleci@latest"
],
"env": {
"CIRCLECI_TOKEN": "YOUR_CIRCLECI_TOKEN",
"CIRCLECI_BASE_URL": "https://circleci.com",
"MAX_MCP_OUTPUT_LENGTH": "50000"
},
"timeout": 60000
}
}
}
Using a Self-Managed Remote MCP Server
Create a wrapper script (e.g. circleci-remote-mcp.sh):
#!/bin/bash
npx mcp-remote http://your-circleci-remote-mcp-server-endpoint:8000/mcp --allow-http
Make it executable, then add it via the MCP configuration UI:
- Access the MCP configuration UI
- Choose the + symbol
- Select scope: global or local
- Enter a name (e.g.
circleci-remote-mcp) - Select transport protocol: stdio
- Enter the command path to your script
- Click Save
Smithery
To install CircleCI MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @CircleCI-Public/mcp-server-circleci --client claude
Demo
Watch it in action
Example: "Find the latest failed pipeline on my branch and get logs" — see the wiki for more examples.
https://github.com/user-attachments/assets/3c765985-8827-442a-a8dc-5069e01edb74
Tool Details
analyze_diff
Analyzes git diffs against cursor rules to identify rule violations.
Provide:
- Git diff content (e.g.
git diff --cached,git diff HEAD) - Repository rules from
.cursorrulesor.cursor/rules
Returns detailed violation reports with confidence scores and explanations.
Useful for:
- Pre-commit code quality checks
- Ensuring consistency with team coding standards
- Catching rule violations before code review
config_helper
Assists with CircleCI configuration tasks by providing guidance and validation.
- Validates your
.circleci/config.ymlfor syntax and semantic errors - Provides detailed validation results and configuration recommendations
- Example: "Validate my CircleCI config"
create_prompt_template
Generates structured prompt templates for AI-enabled applications based on feature requirements.
- Transforms user requirements into optimized prompt templates
- Returns a structured template and a context schema defining required input parameters
- Example: "Create a prompt template for generating bedtime stories by age and topic"
download_usage_api_data
Downloads usage data from the CircleCI Usage API for a given organization. Accepts flexible date input (e.g., "March 2025" or "last month"). Cloud-only feature.
Option 1: Start a new export job by providing:
orgId,startDate,endDate(max 32 days),outputDir
Option 2: Check/download an existing export job by providing:
orgId,jobId,outputDir
Returns a CSV file with CircleCI usage data for the specified time frame.
[!NOTE] Usage data can be fed into the
find_underused_resource_classestool for cost optimization analysis.
find_flaky_tests
Identifies flaky tests in your CircleCI project by analyzing test execution history. Leverages the flaky test detection feature in CircleCI.
This tool can be used in three ways:
-
Using Project Slug (Recommended):
- First use
list_followed_projectsto get your projects, then: - Example: "Get flaky tests for my-project"
- First use
-
Using CircleCI Project URL:
- Example: "Find flaky tests in https://app.circleci.com/pipelines/github/org/repo"
-
Using Local Project Context:
- Works from your local workspace by providing workspace root and git remote URL
- Example: "Find flaky tests in my current project"
Output modes:
- Text (default): Returns flaky test details in text format
- File (requires
FILE_OUTPUT_DIRECTORYenv var): Creates a directory with flaky test details
find_underused_resource_classes
Analyzes a CircleCI usage data CSV file to find jobs with average or max CPU/RAM usage below a given threshold (default: 40%).
Provide a CSV file obtained from download_usage_api_data.
Returns a markdown list of underused jobs organized by project and workflow — useful for identifying cost optimization opportunities.
get_build_failure_logs
Retrieves detailed failure logs from CircleCI builds. This tool can be used in three ways:
-
Using Project Slug and Branch (Recommended):
- First use
list_followed_projectsto get your projects, then: - Example: "Get build failures for my-project on the main branch"
- First use
-
Using CircleCI URLs:
- Provide a failed job URL or pipeline URL directly
- Example: "Get logs from https://app.circleci.com/pipelines/github/org/repo/123"
-
Using Local Project Context:
- Works from your local workspace by providing workspace root, git remote URL, and branch name
- Example: "Find the latest failed pipeline on my current branch"
The tool returns formatted logs including:
- Job names
- Step-by-step execution details
- Failure messages and context
get_job_test_results
Retrieves test metadata for CircleCI jobs, allowing you to analyze test results without leaving your IDE. This tool can be used in three ways:
-
Using Project Slug and Branch (Recommended):
- Example: "Get test results for my-project on the main branch"
-
Using CircleCI URL:
- Job URL:
https://app.circleci.com/pipelines/github/org/repo/123/workflows/abc-def/jobs/789 - Workflow URL:
https://app.circleci.com/pipelines/github/org/repo/123/workflows/abc-def - Pipeline URL:
https://app.circleci.com/pipelines/github/org/repo/123
- Job URL:
-
Using Local Project Context:
- Works from your local workspace by providing workspace root, git remote URL, and branch name
The tool returns:
- Summary of all tests (total, successful, failed)
- Detailed info on failed tests: name, class, file, error message, duration
- List of successful tests with timing
- Filter by test result
[!NOTE] Test metadata must be configured in your CircleCI config. See Collect Test Data for setup instructions.
get_latest_pipeline_status
Retrieves the status of the latest pipeline for a given branch. This tool can be used in three ways:
-
Using Project Slug and Branch (Recommended):
- Example: "Get the status of the latest pipeline for my-project on the main branch"
-
Using CircleCI Project URL:
- Example: "Get the status of the latest pipeline for https://app.circleci.com/pipelines/github/org/repo"
-
Using Local Project Context:
- Works from your local workspace by providing workspace root, git remote URL, and branch name
Example output:
---
Workflow: build
Status: success
Duration: 5 minutes
Created: 4/20/2025, 10:15:30 AM
Stopped: 4/20/2025, 10:20:45 AM
---
Workflow: test
Status: running
Duration: unknown
Created: 4/20/2025, 10:21:00 AM
Stopped: in progress
list_artifacts
Retrieves the list of artifacts produced by a CircleCI job. This tool can be used in three ways:
-
Using Project Slug and Branch (Recommended):
- First use
list_followed_projectsto get your projects, then: - Example: "List artifacts for my-project on the main branch"
- First use
-
Using CircleCI URL:
- Job URL:
https://app.circleci.com/pipelines/gh/organization/project/123/workflows/abc-def/jobs/789 - Workflow URL:
https://app.circleci.com/pipelines/gh/organization/project/123/workflows/abc-def - Pipeline URL:
https://app.circleci.com/pipelines/gh/organization/project/123
- Job URL:
-
Using Local Project Context:
- Works from your local workspace by providing workspace root, git remote URL, and branch name
Useful for:
- Finding download URLs for build artifacts (binaries, reports, logs)
- Checking what artifacts were produced by a pipeline run
list_component_versions
Lists all versions for a specific CircleCI component in an environment. Includes deployment status, commit information, and timestamps.
The tool will prompt you to select the component and environment if not provided.
Useful for:
- Identifying which version is currently live
- Selecting target versions for rollback operations
- Getting deployment details (pipeline, workflow, job)
list_followed_projects
Lists all projects that the user is following on CircleCI.
- Shows all projects you have access to with their
projectSlug - Example: "List my CircleCI projects"
Example output:
Projects followed:
1. my-project (projectSlug: gh/organization/my-project)
2. another-project (projectSlug: gh/organization/another-project)
[!NOTE] The
projectSlug(not the project name) is required for many other CircleCI tools.
recommend_prompt_template_tests
Generates test cases for prompt templates to ensure they produce expected results.
- Creates diverse test scenarios based on your prompt template and context schema
- Returns an array of recommended test cases with various parameter combinations
- Example: "Generate tests for my bedtime story prompt template"
rerun_workflow
Reruns a workflow from its start or from the failed job.
Returns the ID of the newly-created workflow and a link to monitor it.
run_evaluation_tests
Runs evaluation tests (also known as "Prompt Tests") on a CircleCI pipeline. Generates an appropriate CircleCI configuration and triggers a pipeline using it.
This tool can be used in three ways:
-
Using Project Slug and Branch (Recommended):
- First use
list_followed_projectsto get your projects, then: - Example: "Run evaluation tests for my-project on the main branch"
- First use
-
Using CircleCI URL:
- Project URL, Pipeline URL, Workflow URL, or Job URL
- Example: "Run evaluation tests for https://app.circleci.com/pipelines/gh/organization/project/123"
-
Using Local Project Context:
- Works from your local workspace by providing workspace root, git remote URL, and branch name
The tool accepts prompt template files and returns a URL to monitor the triggered pipeline.
[!NOTE] If the project has multiple pipeline definitions, the tool will return a list of available pipelines for you to choose from.
run_pipeline
Triggers a pipeline to run. This tool can be used in three ways:
-
Using Project Slug and Branch (Recommended):
- Example: "Run the pipeline for my-project on the main branch"
-
Using CircleCI URL:
- Pipeline URL, Workflow URL, Job URL, or Project URL with branch
- Example: "Run the pipeline for https://app.circleci.com/pipelines/github/org/repo/123"
-
Using Local Project Context:
- Works from your local workspace by providing workspace root, git remote URL, and branch name
The tool returns a link to monitor the pipeline execution.
run_rollback_pipeline
Triggers a rollback for a CircleCI project. The tool interactively guides you through:
- Project Selection — lists followed projects for you to choose from
- Environment Selection — lists available environments (auto-selects if only one)
- Component Selection — lists available components (auto-selects if only one)
- Version Selection — displays available versions; you select the target for rollback
- Rollback Mode Detection — checks if a rollback pipeline is configured
- Execute Rollback — two options:
- Pipeline Rollback: triggers the rollback pipeline
- Workflow Rerun: reruns a previous workflow using its workflow ID
- Confirmation — summarizes and confirms before execution
Troubleshooting
Quick Fixes
Most common issues:
-
Clear package caches:
npx clear-npx-cache npm cache clean --force -
Force latest version: Add
@latestto your config:"args": ["-y", "@circleci/mcp-server-circleci@latest"] -
Restart your IDE completely (not just reload window)
Authentication Issues
- Invalid token errors: Verify your
CIRCLECI_TOKENin Personal API Tokens - Permission errors: Ensure the token has read access to your projects
- Environment variables not loading: Test with
echo $CIRCLECI_TOKEN(Mac/Linux) orecho %CIRCLECI_TOKEN%(Windows)
Connection and Network Issues
- Base URL: Confirm
CIRCLECI_BASE_URLishttps://circleci.com - Corporate networks: Configure npm proxy settings if behind a firewall
- Firewall blocking: Check if security software blocks package downloads
System Requirements
- Node.js version: Ensure >= 18.0.0 with
node --version - Update Node.js: Consider latest LTS if experiencing compatibility issues
- Package manager: Verify npm/pnpm is working:
npm --version
IDE-Specific Issues
- Config file location: Double-check the path for your OS
- Syntax errors: Validate JSON syntax in your config file
- Console logs: Check the IDE developer console for specific errors
- Try a different IDE: Test in another supported editor to isolate the issue
Process Issues
Hanging processes — kill existing MCP processes:
# Mac/Linux:
pkill -f "mcp-server-circleci"
# Windows:
taskkill /f /im node.exe
Port conflicts: Restart your IDE if the connection seems blocked.
Advanced Debugging
- Test package directly:
npx @circleci/mcp-server-circleci@latest --help - Verbose logging:
DEBUG=* npx @circleci/mcp-server-circleci@latest - Docker fallback: Try Docker installation if npx fails consistently
Still need help?
- Check GitHub Issues for similar problems
- Include your OS, Node version, and IDE when reporting issues
- Share relevant error messages from the IDE console
Telemetry
The server supports OpenTelemetry metrics for tracking tool usage. To disable telemetry, set DISABLE_TELEMETRY=true.
| Metric | Description |
|---|---|
circleci.mcp.tool.invocations | Tool invocation count |
circleci.mcp.tool.duration_ms | Execution time in ms |
circleci.mcp.tool.errors | Error count |
Development
Getting Started
-
Clone the repository:
git clone https://github.com/CircleCI-Public/mcp-server-circleci.git cd mcp-server-circleci -
Install dependencies:
pnpm install -
Build the project:
pnpm build
Building Docker Container
You can build the Docker container locally using:
docker build -t circleci:mcp-server-circleci .
This will create a Docker image tagged as circleci:mcp-server-circleci that you can use with any MCP client.
To run the container locally:
docker run --rm -i -e CIRCLECI_TOKEN=your-circleci-token -e CIRCLECI_BASE_URL=https://circleci.com circleci:mcp-server-circleci
To run the container as a self-managed remote MCP server, add start=remote and optionally specify the port (default: 8000):
docker run --rm -i -e CIRCLECI_TOKEN=your-circleci-token -e CIRCLECI_BASE_URL=https://circleci.com -e start=remote -e port=8000 circleci:mcp-server-circleci
Development with MCP Inspector
The easiest way to iterate on the MCP Server is using the MCP inspector. You can learn more about the MCP inspector at https://modelcontextprotocol.io/docs/tools/inspector
-
Start the development server:
pnpm watch # Keep this running in one terminal -
In a separate terminal, launch the inspector:
pnpm inspector -
Configure the environment:
- Add your
CIRCLECI_TOKENto the Environment Variables section in the inspector UI - The token needs read access to your CircleCI projects
- Optionally set your CircleCI Base URL (defaults to
https://circleci.com)
- Add your
Testing
-
Run the test suite:
pnpm test -
Run tests in watch mode during development:
pnpm test:watch
For more detailed contribution guidelines, see CONTRIBUTING.md
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portkey-admin-mcp
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Web Accessibility Testing (A11y MCP)
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BCMS MCP
Give me a one - two sentence description of the BCMS MCP # MCP The BCMS Model Context Protocol (MCP) integration enables AI assistants like Claude, Cursor, and other MCP-compatible tools to interact directly with your BCMS content. This allows you to create, read, and update content entries, manage media files, and explore your content structure—all through natural language conversations with AI. ## What is MCP? The [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) is an open standard developed by Anthropic that allows AI applications to securely connect to external data sources and tools. With BCMS MCP support, you can leverage AI assistants to: - Query and explore your content structure - Create new content entries with AI-generated content - Update existing entries - Manage your media library - Get intelligent suggestions based on your content model --- ## Getting Started ### Prerequisites 1. A BCMS account with an active instance 2. An MCP key with appropriate permissions 3. An MCP-compatible client (Claude Desktop, Cursor, or any MCP client) ### Step 1: Create an MCP Key 1. Navigate to your BCMS dashboard 2. Go to Settings → MCP 3. Click Create MCP Key 4. Configure the permissions for templates you want the AI to access:GET: Read entries 5. POST: Create entries 6. PUT: Update entries 7. DELETE: Delete entries Note: Right now, MCP only supports creating, reading and updating content. ### Step 2: Configure Your MCP Client You can find full instructions for integrating BCMS with your AI tools right inside BCMS, on the MCP page. But in general, installing BCMS MCP works in a standard way: ``` { "mcpServers": { "bcms": { "url": "https://app.thebcms.com/api/v3/mcp?mcpKey=YOUR_MCP_KEY" } } } ``` ## Available Tools Once connected, your AI assistant will have access to the following tools based on your MCP key permissions: ### Content Discovery #### list_templates_and_entries Lists all templates and their entries that you have access to. This is typically the first tool to call when exploring your BCMS content. Returns: - Template IDs, names, and slugs - Entry IDs with titles and slugs for each language Example prompt: "Show me all the templates and entries in my BCMS" --- ### Entry Management #### list_entries_for_{templateId} Retrieves all entries for a specific template with full content data. A separate tool is generated for each template you have access to. Returns: - Complete entry data including all meta fields - Content in all configured languages - Entry statuses Example prompt: "List all blog posts from my Blog template" --- #### create_entry_for_{templateId} Creates a new entry for a specific template. The input schema is dynamically generated based on your template's field structure. Input: - statuses: Array of status assignments per language - meta: Array of metadata for each language (title, slug, custom fields) - content: Array of content nodes for each language Example prompt: "Create a new blog post titled 'Getting Started with BCMS' with a brief introduction paragraph" --- #### update_entry_for_{templateId} Updates an existing entry for a specific language. Input: - entryId: The ID of the entry to update - lng: Language code (e.g., "en") - status: Optional status ID - meta: Updated metadata - content: Updated content nodes Example prompt: "Update the introduction paragraph of my 'Getting Started' blog post" --- ### Media Management #### list_all_media Lists all media files in your media library. Returns: - Media IDs, names, and types - File metadata (size, dimensions for images) - Parent directory information Example prompt: "Show me all images in my media library" --- #### list_media_dirs Lists the directory structure of your media library. Returns: - Hierarchical directory structure - Directory IDs and names Example prompt: "Show me the folder structure of my media library" --- #### create-media-directory Creates a new directory in your media library. Input: - name: Name of the directory - parentId: Optional parent directory ID (root if not specified) Example prompt: "Create a new folder called 'Blog Images' in my media library" --- #### request-upload-media-url Returns a URL you use to upload a file (for example via POST with multipart form data), which avoids pushing large binaries through the MCP tool payload. You still need a valid file name and MIME type when uploading, as described in the tool response. Availability: Only when the MCP key has Can mutate media enabled. Example prompt: “Give me an upload URL for a new hero image, then tell me how to upload it.” Input: - fileName: Name of the file with extension - fileData: Base64-encoded file data (with data URI prefix) - parentId: Optional parent directory ID Example prompt: "Upload this image to my Blog Images folder" --- ### Linking Tools #### get_entry_pointer_link Generates an internal BCMS link to an entry for use in content. Input: - entryId: The ID of the entry to link to Returns: - Internal link format: entry:{entryId}@*_{templateId}:entry Example prompt: "Get me the internal link for the 'About Us' page entry" --- #### get_media_pointer_link Generates an internal BCMS link to a media item for use in content. Input: - mediaId: The ID of the media item Returns: - Internal link format: media:{mediaId}@*_@*_:entry Example prompt: "Get the link for the hero image so I can use it in my blog post" --- ## Content Structure ### Entry Content Nodes When creating or updating entries, content is structured as an array of nodes. Supported node types include: Type Description paragraph Standard text paragraph heading Heading (h1-h6) bulletList Unordered list orderedList Numbered list listItem List item codeBlock Code block with syntax highlighting blockquote Quote block image Image node widget Custom widget with props ### Example Content Structure ``` { "content": [ { "lng": "en", "nodes": [ { "type": "heading", "attrs": { "level": 1 }, "content": [ { "type": "text", "text": "Welcome to BCMS" } ] }, { "type": "paragraph", "content": [ { "type": "text", "text": "This is your first paragraph." } ] } ] } ] } ``` ## Security & Permissions ### MCP Key Scopes Your MCP key controls what the AI can access: - Template Access: Only templates explicitly granted in the MCP key are visible - Operation Permissions: Each template can have independent GET/POST/PUT/DELETE permissions - Media Access: Media operations are controlled separately ### Best Practices 1. Principle of Least Privilege: Only grant the permissions needed for your use case 2. Separate Keys: Create different MCP keys for different purposes or team members 3. Regular Rotation: Periodically rotate your MCP keys ## Use Cases ### Content Creation Workflows Blog Post Creation "Create a new blog post about the benefits of headless CMS. Include an introduction, three main benefits with explanations, and a conclusion. Use the Blog template." Product Updates "Update the price field for all products in the Electronics category to apply a 10% discount" ### Content Exploration Content Audit "List all blog posts that don't have a featured image set" Translation Status "Show me which entries are missing German translations" ### Media Organization Library Cleanup "Show me all unused images in the media library" Folder Setup "Create folder structure for: Products > Categories > Electronics, Clothing, Home" ## Troubleshooting ### Common Issues #### "MCP key not found" - Verify your MCP key format: keyId.keySecret.instanceId - Ensure the MCP key hasn't been deleted or deactivated - Check that you're using the correct instance #### "MCP key does not have access to template" - Review your MCP key permissions in the dashboard - Ensure the required operation (GET/POST/PUT/DELETE) is enabled for the template #### Session Expired - MCP sessions may timeout after periods of inactivity - Simply start a new conversation to establish a fresh session ### Getting Help - Documentation: [thebcms.com/docs](https://thebcms.com/docs) - Support: [[email protected]](mailto:[email protected]) - Community: [Join BCMS Discord](https://discord.com/invite/SYBY89ccaR) for community support ## Technical Reference ### Endpoint POST https://app.thebcms.com/api/v3/mcp?mcpKey={MCP_KEY} ### Transport BCMS MCP uses the Streamable HTTP transport with session management. Sessions are maintained via the mcp-session-id header. ### Response Format All tools return structured JSON responses conforming to the MCP specification with: - content: Array of content blocks - structuredContent: Typed response data ## Rate Limits MCP requests are subject to the same rate limits as API requests: - Requests are tracked per MCP key - Contact support if you need higher limits for production workloads
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