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. Set up the connector

   Register your Context7 MCP credentials with Scalekit so it can authenticate requests on your behalf. You do this once per environment.

   Dashboard setup steps

   Register your Context7 API key with Scalekit so it can authenticate and proxy documentation requests on behalf of your users. Context7 MCP uses API key authentication — there is no redirect URI or OAuth flow.

   1. Get a Context7 API key

      • Go to context7.com and sign in to your account.
      • Navigate to the API Keys section in the dashboard.
      • Click Create API Key… and give it a name (e.g. Agent Auth).
      • Copy the generated key — it starts with ctx7sk-.

      

   2. Create a connection in Scalekit

      • In the Scalekit dashboard, go to AgentKit → Connections → Create Connection.
      • Search for Context7 MCP and click Create.
      • Note the Connection name — use this as connection_name in your code (e.g., context7mcp).

   3. Add a connected account

      Connected accounts link a specific user identifier in your system to a Context7 API key. Add them via the dashboard for testing, or via the Scalekit API in production.

      Via dashboard (for testing)

      • Open the connection and click the Connected Accounts tab → Add account.
      • Fill in Your User’s ID and API Key, then click Save.

      Via API (for production)

      Node.js

      await scalekit.connect.upsertConnectedAccount({
        connectionName: 'context7mcp',
        identifier: 'user@example.com',
        credentials: { apiKey: 'ctx7sk-...' },
      })

      Python

      scalekit_client.connect.upsert_connected_account(
          connection_name="context7mcp",
          identifier="user@example.com",
          credentials={"api_key": "ctx7sk-..."},
      )

4. 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.

NameTypeRequiredDescription

libraryIdstringrequiredThe Context7-compatible library ID (e.g. '/vercel/next.js', '/mongodb/docs')

querystringrequiredThe user's question or task to retrieve relevant documentation for

schema_versionstringoptionalOptional schema version to use for tool execution

tool_versionstringoptionalOptional 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.

NameTypeRequiredDescription

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

querystringrequiredThe user's question or task to help rank library results by relevance

schema_versionstringoptionalOptional schema version to use for tool execution

tool_versionstringoptionalOptional tool version to use for tool execution