Cala
Cala turns internet chaos into structured, verified knowledge that AI agents and LLMs can call as a tool.
Documentation Index
Fetch the complete documentation index at: https://docs.cala.ai/llms.txt Use this file to discover all available pages before exploring further.
MCP
Connect your AI agent to Cala's MCP
https://api.cala.ai/mcp/
For more information about MCP and how it works, you can read more about it here.
Connect your agent to Cala's MCP
You can use Cala via our MCP. To get started, you need to get an API key to authenticate your MCP client. Go to our Console and create a new API key.
Create a free Cala account and get your API key.With your API key in hand, you can connect your AI agent such as Cursor, Claude Desktop and others to our MCP server. Cala MCP gives AI agents access to verified, structured and typed knowledge — both as natural-language answers and structured data — as well as entity information.
Add to `~/.cursor/mcp.json`:```json theme={null}
{
"mcpServers": {
"Cala": {
"url": "https://api.cala.ai/mcp/",
"headers": {
"X-API-KEY": "YOUR_CALA_API_KEY"
}
}
}
}
```
For more information, follow their documentation [here](https://cursor.com/docs/context/mcp#installing-mcp-servers).
Go to Settings → Developer → Edit Config and add the following JSON to the existing config file:
```json theme={null}
{
"mcpServers": {
"Cala": {
"command": "npx",
"args": [
"mcp-remote",
"https://api.cala.ai/mcp/",
"--header",
"X-API-KEY: YOUR_CALA_API_KEY"
]
}
}
}
```
For more information, follow their documentation [here](https://support.claude.com/en/articles/11175166-getting-started-with-custom-connectors-using-remote-mcp).
An example of the final config file could be:
```json theme={null}
{
"preferences": {
"coworkWebSearchEnabled": true
},
"mcpServers": {
"cala": {
"command": "npx",
"args": [
"mcp-remote",
"https://api.cala.ai/mcp/",
"--header",
"X-API-KEY: YOUR_CALA_API_KEY"
]
}
}
}
```
Add to `.vscode/mcp.json`:
```json theme={null}
{
"servers": {
"Cala": {
"type": "http",
"url": "https://api.cala.ai/mcp/",
"headers": {
"X-API-KEY": "YOUR_CALA_API_KEY"
}
}
}
}
```
For more information, follow their documentation [here](https://code.visualstudio.com/docs/copilot/customization/mcp-servers)
To support the full power of our graph's flexible schema, this MCP server utilizes dynamic JSON objects. This provides a "schema-less" experience for the LLM. Because of this, it is incompatible with OpenAI's "strict mode" so please ensure `strict: false` is set in your OpenAI specification.
For more information, follow their documentation [here](https://developers.openai.com/api/docs/guides/tools-connectors-mcp)
For clients with built-in remote MCP support:
```json theme={null}
{
"mcpServers": {
"Cala": {
"url": "https://api.cala.ai/mcp/",
"headers": {
"X-API-KEY": "YOUR_CALA_API_KEY"
}
}
}
}
```
For clients without built-in remote MCP support:
```json theme={null}
{
"mcpServers": {
"Cala": {
"command": "npx",
"args": [
"mcp-remote",
"https://api.cala.ai/mcp/",
"--header",
"X-API-KEY: YOUR_CALA_API_KEY"
]
}
},
}
```
Available Tools
Here are the tools available to the Cala MCP:
Get a succinct, token-optimized answer in natural-language markdown, with sources, explainability, and matching entities. Accepts either a natural-language question or a Cala QL expression as input. Get verified knowledge as structured, typed JSON rows plus matching entities. Accepts either a Cala QL expression or a natural-language question as input. Search entities by name with fuzzy matching. Get the field schema for an entity by its UUID. Returns the available properties, relationships, and numerical observations you can use when querying an entity. Retrieve information about an entity by its UUID.Hubs & Marketplaces
You can also find Cala's MCP server listed on the following hubs and marketplaces:
Browse Cala's MCP server listing on mcpservers.org.相关服务器
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