SidClaw GovernanceMCPServer
Governance proxy for MCP servers — wraps any server with policy evaluation, human approval workflows, and hash-chain audit trails.
SidClaw
Approve, deny, and audit AI agent tool calls.
Works with MCP, LangChain, OpenAI Agents, Claude Agent SDK, and 15+ more.
Website · Documentation · Live Demo · SDK on npm · SDK on PyPI
Your agents call tools without oversight. SidClaw intercepts every tool call, checks it against your policies, and holds risky actions for human review before they execute.
Try it locally (self-contained, no install)
Clone and run:
git clone https://github.com/sidclawhq/platform
cd platform/packages/sidclaw-demo && node cli.mjs
Opens a local governance dashboard at http://localhost:3030 with four pre-loaded scenarios (Claude Code rm -rf, fintech trade, DevOps scale-to-zero, clinical lab order). No signup, no Docker, no API key — just the approval card UX running in your browser.
Coming to npm soon:
npx sidclaw-demoone-liner will be published alongside the next SDK release. Until then, the clone-and-run path above is the canonical way to see the demo.
See it in action

Agent wants to send an email → policy flags it → reviewer sees full context → approves or denies → trace recorded.
Works With Your Stack

SidClaw integrates with 18+ frameworks and platforms — including OpenClaw (329K+ users), LangChain, OpenAI, MCP, Claude Agent SDK, Google ADK, NemoClaw, Copilot Studio, GitHub Copilot, and more. Add governance in one line of code. See all integrations →
See It In Action
Customer Support Agent (Financial Services)

An AI agent wants to send a customer email. Policy flags it for review. The reviewer sees full context — who, what, why — and approves with one click. Every step is traced.
Infrastructure Automation (DevOps)

An AI agent wants to scale production services. High-risk deployments require human approval. Read-only monitoring is allowed instantly.
Clinical Decision Support (Healthcare)

An AI assistant recommends lab orders. The physician reviews the clinical context and approves. Medication prescribing is blocked by policy — only physicians can prescribe.
How It Works
Agent wants to act → SidClaw evaluates → Policy decides → Human approves (if needed) → Action executes → Trace recorded
Four primitives govern every agent action:
┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐
│ Identity │ → │ Policy │ → │ Approval │ → │ Trace │
│ │ │ │ │ │ │ │
│ Every │ │ Every │ │ High-risk│ │ Every │
│ agent │ │ action │ │ actions │ │ decision │
│ has an │ │ evaluated│ │ get human│ │ creates │
│ owner & │ │ against │ │ review │ │ tamper- │
│ scoped │ │ explicit │ │ with rich│ │ proof │
│ perms │ │ rules │ │ context │ │ audit │
└──────────┘ └──────────┘ └──────────┘ └──────────┘
- allow → action executes immediately, trace recorded
- approval_required → human sees context card, approves/denies, trace recorded
- deny → blocked before execution, no data accessed, trace recorded
Deploy your own SidClaw instance ($0)
Railway is the recommended one-click deploy — it spins up Postgres + API + Dashboard together. Vercel hosts only the Next.js dashboard; pair it with a hosted API.
Vercel (dashboard only — point at an existing SidClaw API)
https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2Fsidclawhq%2Fplatform&root-directory=apps%2Fdashboard&env=NEXT_PUBLIC_API_URL&envDescription=Your%20SidClaw%20API%20base%20URL%20(e.g.%20https%3A%2F%2Fapi.sidclaw.com)
Vercel can only host the dashboard (Next.js). The API is Fastify — deploy it to Railway, Fly, Render, or run via Docker. Set NEXT_PUBLIC_API_URL on the dashboard project to point at it.
Under 3 minutes to a working instance on Railway.
Quick Start — Pick What Fits
Option 1: Claude Code Hooks (zero code)
For Claude Code users. Every Bash, Write, Agent, mcp__* tool call is governed by SidClaw:
# In the SidClaw platform repo
npm run hooks:install
# Then set two env vars
export SIDCLAW_BASE_URL=https://api.sidclaw.com
export SIDCLAW_API_KEY=ai_your_key_here
Restart Claude Code. rm -rf pauses for approval, git push --force gets flagged, every tool call is traced with a hash-chained audit trail. See hooks/README.md.
Option 2: create-sidclaw-app (interactive scaffold)
npx create-sidclaw-app my-agent
cd my-agent
npm start
Option 3: MCP Governance Proxy (zero code, wraps any MCP server)
Jump to the MCP Governance Proxy section below.
Option 4: SDK wrapper (one line per tool)
// Before: the agent decides, nobody reviews
await sendEmail({ to: "[email protected]", subject: "Follow-up", body: "..." });
// After: wrap with SidClaw — now policies apply
const sendEmail = withGovernance(client, {
operation: 'send_email',
data_classification: 'confidential',
}, sendEmailFn);
await sendEmail({ to: "[email protected]", subject: "Follow-up", body: "..." });
// → allow (executes) | approval_required (human reviews) | deny (blocked)
Same thing in Python
@with_governance(client, GovernanceConfig(
operation="send_email",
data_classification="confidential",
))
def send_email(to, subject, body):
email_service.send(to=to, subject=subject, body=body)
Full TypeScript example with imports
npm install @sidclaw/sdk
import { AgentIdentityClient, withGovernance } from '@sidclaw/sdk';
const client = new AgentIdentityClient({
apiKey: process.env.SIDCLAW_API_KEY,
apiUrl: 'https://api.sidclaw.com',
agentId: process.env.SIDCLAW_AGENT_ID,
});
const sendEmail = withGovernance(client, {
operation: 'send_email',
target_integration: 'email_service',
resource_scope: 'customer_emails',
data_classification: 'confidential',
}, async (to, subject, body) => {
await emailService.send({ to, subject, body });
});
await sendEmail('[email protected]', 'Follow-up', 'Hello...');
// allow → executes | approval_required → waits for human | deny → throws
Full Python example with imports
pip install sidclaw
import os
from sidclaw import SidClaw
from sidclaw.middleware.generic import with_governance, GovernanceConfig
client = SidClaw(
api_key=os.environ["SIDCLAW_API_KEY"],
agent_id=os.environ["SIDCLAW_AGENT_ID"],
)
@with_governance(client, GovernanceConfig(
operation="send_email",
target_integration="email_service",
data_classification="confidential",
))
def send_email(to, subject, body):
email_service.send(to=to, subject=subject, body=body)
MCP Governance Proxy
Wrap any MCP server with policy evaluation and approval workflows. Works with Claude Desktop, Cursor, VS Code, GitHub Copilot — any MCP client. Listed on the official MCP Registry.
Add to your .mcp.json:
{
"mcpServers": {
"postgres-governed": {
"command": "npx",
"args": ["-y", "@sidclaw/sdk", "sidclaw-mcp-proxy", "--transport", "stdio"],
"env": {
"SIDCLAW_API_KEY": "ai_your_key",
"SIDCLAW_AGENT_ID": "your-agent-id",
"SIDCLAW_UPSTREAM_CMD": "npx",
"SIDCLAW_UPSTREAM_ARGS": "-y,@modelcontextprotocol/server-postgres,postgresql://localhost/mydb"
}
}
}
}
SELECT * FROM customers→ allowed (~50ms overhead)DELETE FROM customers WHERE id = 5→ held for human approvalDROP TABLE customers→ denied by policy
Why not just auth / sandboxing / logging?
| Approach | What it solves | What it doesn't solve |
|---|---|---|
| Auth (Okta, OAuth) | Who is this agent? | Should this specific action execute right now? |
| Sandboxing (Docker, WASM) | Blast radius if something goes wrong | Whether the action should happen at all |
| Logging (Langfuse, LangSmith) | What happened after the fact | Intercepting actions before they execute |
| Policy engines (OPA) | General-purpose policy evaluation | Approval workflows, agent-specific context, audit trails |
| SidClaw | All of the above, plus the Approval primitive | — |
SidClaw sits at the tool-call layer: the moment an agent decides to act in the real world.
Integrations
SidClaw wraps your existing agent tools — no changes to your agent logic.
Agent Frameworks
| TypeScript | Python | |
|---|---|---|
| Core client | @sidclaw/sdk | sidclaw |
| MCP proxy | @sidclaw/sdk/mcp | sidclaw.mcp |
| LangChain | @sidclaw/sdk/langchain | sidclaw.middleware.langchain |
| OpenAI Agents | @sidclaw/sdk/openai-agents | sidclaw.middleware.openai_agents |
| CrewAI | @sidclaw/sdk/crewai | sidclaw.middleware.crewai |
| Vercel AI | @sidclaw/sdk/vercel-ai | — |
| Pydantic AI | — | sidclaw.middleware.pydantic_ai |
| Claude Agent SDK | @sidclaw/sdk/claude-agent-sdk | sidclaw.middleware.claude_agent_sdk |
| Google ADK | @sidclaw/sdk/google-adk | sidclaw.middleware.google_adk |
| LlamaIndex | @sidclaw/sdk/llamaindex | sidclaw.middleware.llamaindex |
| Composio | @sidclaw/sdk/composio | sidclaw.middleware.composio |
| NemoClaw | @sidclaw/sdk/nemoclaw | sidclaw.middleware.nemoclaw |
| Webhooks | @sidclaw/sdk/webhooks | sidclaw.webhooks |
Platform Integrations
| Integration | Description |
|---|---|
| Claude Code | Govern any MCP server in Claude Code. Add a .mcp.json entry — zero code changes. Guide → |
| OpenClaw | Governance proxy for OpenClaw skills. Published as sidclaw-governance on ClawHub. Guide → |
| MCP | Governance proxy for any MCP server. Listed on the official MCP Registry. CLI binary (sidclaw-mcp-proxy) + programmatic API. Guide → |
| NemoClaw | Govern NVIDIA NemoClaw sandbox tools with MCP-compatible proxy generation. Guide → |
| Copilot Studio | Governance for Microsoft Copilot Studio skills via OpenAPI action. Guide → |
| GitHub Copilot | Governance for GitHub Copilot agents via HTTP transport. Guide → |
| GitHub Action | sidclawhq/governance-action@v1 — reusable CI governance step. Guide → |
Notification Channels
Approval requests are delivered to your team's preferred channels. Reviewers can approve or deny directly from chat.
| Channel | Features |
|---|---|
| Slack | Block Kit messages with interactive Approve/Deny buttons. Messages update in-place after decision. |
| Microsoft Teams | Adaptive Card notifications with Approve/Deny buttons (Bot Framework) or dashboard links (webhook). |
| Telegram | HTML messages with inline keyboard. Callback updates remove buttons and add reply. |
| Resend | Email notifications for approval requests via transactional email. |
Licensing
| Component | License | What you can do |
|---|---|---|
SDK (@sidclaw/sdk, sidclaw on PyPI) | Apache 2.0 | Use freely, modify, distribute, commercial use |
MCP Proxy (sidclaw-mcp-proxy) | Apache 2.0 | Same as SDK |
| Platform (API, Dashboard, Docs) | FSL 1.1 | Free for orgs under CHF 1M revenue. Converts to Apache 2.0 in 2028 |
Start with just the SDK? You don't need the platform. The SDK works standalone with the free hosted API at app.sidclaw.com, or you can self-host everything.
Why This Exists
AI agents are being deployed in production, but the governance layer is missing:
- 73% of CISOs fear AI agent risks, but only 30% are ready (NeuralTrust 2026)
- 79% of enterprises have blind spots where agents act without oversight
- FINRA 2026 explicitly requires "documented human checkpoints" for AI agent actions in financial services
- EU AI Act (August 2026) mandates human oversight, automatic logging, and risk management for high-risk AI systems
- OpenClaw has 329K+ stars and 13,700+ skills — but 1,184 malicious skills were found in the ClawHavoc campaign. There's no policy layer governing what skills can do.
The big vendors (Okta, SailPoint, WorkOS) handle identity and authorization. But none of them ship the approval step — the part where a human sees rich context and makes an informed decision before an agent acts.
Compliance
SidClaw maps to regulatory requirements across the US, EU, Switzerland, and Singapore:
🇺🇸 FINRA 2026 · 🇪🇺 EU AI Act · 🇨🇭 FINMA · 🇸🇬 MAS TRM · 🇺🇸 NIST AI RMF · 🌐 OWASP Agentic
Platform Features
For Developers
- 60-second setup —
npx create-sidclaw-appscaffolds a working governed agent - <50ms evaluation overhead — the governance layer is invisible to your users
- 5-minute integration — wrap existing tools, no code changes
- MCP-native — governance proxy for any MCP server
- Framework-agnostic — LangChain, Vercel AI, OpenAI, CrewAI, Pydantic AI, Composio, Claude Agent SDK, Google ADK, LlamaIndex, NemoClaw, or plain functions
- Typed SDKs — TypeScript (npm) + Python (PyPI)
For Security & Compliance Teams
- Policy engine — allow / approval_required / deny with priority ordering and classification hierarchy
- Approval workflow — context-rich cards with agent reasoning, risk classification, and separation of duties
- Audit trails — correlated traces with integrity hash chains (tamper-proof)
- SIEM export — JSON and CSV, continuous webhook delivery
For Platform Teams
- RBAC — admin, reviewer, viewer roles with enforced permissions
- Tenant isolation — automatic tenant scoping on every query
- API key management — scoped keys with rotation
- Rate limiting — per-tenant, per-endpoint-category
- Webhooks — real-time notifications for approvals, traces, lifecycle events
- Chat integrations — approve/deny from Slack, Teams, or Telegram without opening the dashboard
- Self-serve signup — GitHub, Google, email/password
Architecture
┌─────────────┐ ┌──────────────┐ ┌──────────────────┐
│ Your Agent │ │ SidClaw SDK │ │ SidClaw API │
│ │ ──► │ │ ──► │ │
│ LangChain │ │ evaluate() │ │ Policy Engine │
│ MCP Server │ │ withGovern() │ │ Approval Service │
│ OpenAI SDK │ │ governTools()│ │ Trace Store │
│ Any tool │ │ │ │ Webhook Delivery │
└─────────────┘ └──────────────┘ └──────────────────┘
│
┌────────┴────────┐
▼ ▼
┌──────────────┐ ┌──────────────┐
│ Dashboard │ │ Notifications│
│ │ │ │
│ Agents │ │ Slack │
│ Policies │ │ Teams │
│ Approvals │ │ Telegram │
│ Traces │ │ Email │
│ Settings │ │ Webhooks │
└──────────────┘ └──────────────┘
Deploy
One-Click Deploy
Deploy from the GitHub repo to Railway. Add a PostgreSQL database, configure environment variables, and you're live.
Deploy the dashboard to Vercel (requires a separately hosted API).
Self-Host (Docker)
curl -sSL https://raw.githubusercontent.com/sidclawhq/platform/main/deploy/self-host/setup.sh | bash
Or manually:
git clone https://github.com/sidclawhq/platform.git
cd platform
cp deployment/env.example .env # edit with your values
docker compose -f docker-compose.production.yml up -d
Development credentials:
- Email:
[email protected]/ Password:admin - Or click "Sign in with SSO" on the login page to auto-login without a password
Hosted Cloud
No infrastructure to manage. Start free at app.sidclaw.com
See deployment documentation for production configuration, environment variables, and upgrade guides.
Documentation
- Quick Start — 2 minutes to first governed action
- SDK Reference — every method documented
- Integrations — MCP, OpenClaw, NemoClaw, LangChain, OpenAI, Claude Agent SDK, Google ADK, Copilot Studio, GitHub Copilot, and more
- Policy Guide — authoring, versioning, testing
- Compliance — 🇺🇸 FINRA · 🇪🇺 EU AI Act · 🇨🇭 FINMA · 🇸🇬 MAS TRM · 🇺🇸 NIST AI RMF · 🌐 OWASP
- API Reference — every endpoint
Contributing
We welcome contributions! See CONTRIBUTING.md for guidelines.
The SDK (packages/sdk/) is Apache 2.0. The platform (apps/) is FSL 1.1.
License
- SDK (
packages/sdk/,packages/shared/): Apache License 2.0 — use freely for any purpose - Platform (
apps/api/,apps/dashboard/,apps/docs/,apps/landing/,apps/demo*/): Functional Source License 1.1 — source-available. Cannot offer as a competing hosted service. Converts to Apache 2.0 after 2 years (March 2028).
Links
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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. 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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. 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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. 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