Context7 MCP connector

1. Install the SDK

   Node.js

   npm install @scalekit-sdk/node

   Python

   pip install scalekit

   Full SDK reference: Node.js | Python

2. Set your credentials

   Add your Scalekit credentials to your .env file. Find values in app.scalekit.com > Developers > API Credentials.

   .env

   SCALEKIT_ENVIRONMENT_URL=<your-environment-url>
   SCALEKIT_CLIENT_ID=<your-client-id>
   SCALEKIT_CLIENT_SECRET=<your-client-secret>

3. Make your first call

   Node.js

   quickstart.ts

   import { ScalekitClient } from '@scalekit-sdk/node'
   import 'dotenv/config'
   
   const scalekit = new ScalekitClient(
     process.env.SCALEKIT_ENV_URL,
     process.env.SCALEKIT_CLIENT_ID,
     process.env.SCALEKIT_CLIENT_SECRET,
   )
   const actions = scalekit.actions
   
   const connector = 'context7mcp'
   const identifier = 'user_123'
   
   // Make your first call
   const result = await actions.executeTool({
     connector,
     identifier,
     toolName: 'context7mcp_query_docs',
     toolInput: { libraryId: 'YOUR_LIBRARYID', query: 'YOUR_QUERY' },
   })
   console.log(result)

   Python

   quickstart.py

   import os
   from scalekit.client import ScalekitClient
   from dotenv import load_dotenv
   load_dotenv()
   
   scalekit_client = ScalekitClient(
       env_url=os.getenv("SCALEKIT_ENV_URL"),
       client_id=os.getenv("SCALEKIT_CLIENT_ID"),
       client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
   )
   actions = scalekit_client.actions
   
   connection_name = "context7mcp"
   identifier = "user_123"
   
   # Make your first call
   result = actions.execute_tool(
       tool_input={"libraryId":"YOUR_LIBRARYID","query":"YOUR_QUERY"},
       tool_name="context7mcp_query_docs",
       connection_name=connection_name,
       identifier=identifier,
   )
   print(result)

What you can do

Connect this agent connector to let your agent:

• Id resolve library — Search for a library by name and resolve it to a Context7-compatible library ID
• Query docs — Fetch up-to-date, version-specific documentation and code examples for a library using its Context7 ID

Tool list

Use the exact tool names from the Tool list below when you call execute_tool. If you’re not sure which name to use, list the tools available for the current user first.

context7mcp_query_docs # Fetch up-to-date, version-specific documentation and code examples for a library using its Context7 ID. Returns relevant docs for the given query to help answer questions about a specific library, API, or framework. 4 params ▾

Fetch up-to-date, version-specific documentation and code examples for a library using its Context7 ID. Returns relevant docs for the given query to help answer questions about a specific library, API, or framework.

Name Type Required Description

libraryId string required The Context7-compatible library ID (e.g. '/vercel/next.js', '/mongodb/docs')

query string required The user's question or task to retrieve relevant documentation for

schema_version string optional Optional schema version to use for tool execution

tool_version string optional Optional tool version to use for tool execution

context7mcp_resolve_library_id # Search for a library by name and resolve it to a Context7-compatible library ID. Use this before calling context7mcp_query_docs when you have a library name but not its Context7 ID. 4 params ▾

Search for a library by name and resolve it to a Context7-compatible library ID. Use this before calling context7mcp_query_docs when you have a library name but not its Context7 ID.

Name Type Required Description

libraryName string required The name of the library or framework to search for (e.g. 'Next.js', 'React', 'MongoDB')

query string required The user's question or task to help rank library results by relevance

schema_version string optional Optional schema version to use for tool execution

tool_version string optional Optional tool version to use for tool execution