> **Building with AI coding agents?** Install the authstack plugin with one command. This equips your agent with accurate Scalekit implementation patterns.
>
> **Recommended** (the `-y` flags skip prompts, so the command runs without an interactive terminal):
> ```bash
> npx -y @scalekit-inc/cli setup -y
> ```
>
> Global:
> ```bash
> npm install -g @scalekit-inc/cli
> scalekit setup -y
> ```
>
> Supports Claude Code, Cursor, GitHub Copilot, Codex + skills for other Agent Skills-compatible agents in `~/.agents/skills`.
> Skills: integrate-agentkit, implement-saaskit, add-mcp-oauth, implement-sso, implement-scim.
> [Full setup guide](https://docs.scalekit.com/dev-kit/build-with-ai/)

---

# Connect AI agents to the Context7 MCP server

The Context7 MCP connector routes your AI agent's tool calls to Context7's own MCP server through Scalekit. Each user connects their own Context7 API key once, and Scalekit sends it with every call, so your agent never handles credentials. It comes with 2 tools.

**Authentication:** API Key
**Categories:** AI, Developer Tools, Productivity
**Tools:** 2: 2 read, 0 write, 0 destructive
**Users sign in with:** API key
**Built by:** Vendor MCP
**Try it:** [Playground in the Scalekit dashboard](https://app.scalekit.com/ws/signup?sk_intent=playground&provider=CONTEXT7MCP)

## Setup

1. ### Install the SDK

   **Node.js**

   ```bash
   npm install @scalekit-sdk/node dotenv
   ```

   **Python**

   ```bash
   pip install scalekit-sdk-python python-dotenv
   ```

2. ### Set your credentials

   Add your Scalekit credentials to your `.env` file. Find values in **[app.scalekit.com](https://app.scalekit.com)** > **Developers** > **API Credentials**.

   ```sh title=".env"
   SCALEKIT_ENVIRONMENT_URL=<your-environment-url>
   SCALEKIT_CLIENT_ID=<your-client-id>
   SCALEKIT_CLIENT_SECRET=<your-client-secret>
   ```

3. ### Create the Context7 MCP connection

   In **AgentKit > Connections**, create a Context7 MCP connection. The name you give it is the `connection_name` your code passes. See [Configure connections](/agentkit/connections/).

   **Console steps with screenshots:**

   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.

   1. ### Get a Context7 API key

      - Go to [context7.com](https://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-`.

      > Image: Context7 dashboard showing the API Keys section with an existing key and the Create API Key button

   2. ### Create a connection in Scalekit

      - In the [Scalekit dashboard](https://app.scalekit.com), 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 one in the dashboard to test. In production, each user adds their own through the authorization link: they enter their credentials on the page it opens.

      **In the dashboard, to test**

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

      **From your backend, if your app already has the credentials**

      For example, when users enter them on a settings page in your app:

        **Node.js**

        ```ts
        import { ConnectorStatus } from '@scalekit-sdk/node'

        const authorizationDetails = {
          details: {
            case: 'staticAuth',
            value: { details: { api_key: 'ctx7sk-...' } },
          },
        }

        let { connectedAccount } = await scalekit.actions.upsertConnectedAccount({
          connectionName: 'context7mcp',
          identifier: 'user_123',
          authorizationDetails,
        })

        // Make sure the account is ACTIVE before the first tool call.
        if (connectedAccount?.status !== ConnectorStatus.ACTIVE) {
          ;({ connectedAccount } = await scalekit.actions.upsertConnectedAccount({
            connectionName: 'context7mcp',
            identifier: 'user_123',
            authorizationDetails,
          }))
        }
        ```

        **Python**

        ```python
        authorization_details = {"static_auth": {"api_key": "ctx7sk-..."}}

        response = scalekit_client.actions.upsert_connected_account(
            connection_name="context7mcp",
            identifier="user_123",
            authorization_details=authorization_details,
        )

        # Make sure the account is ACTIVE before the first tool call.
        if response.connected_account.status != "ACTIVE":
            response = scalekit_client.actions.upsert_connected_account(
                connection_name="context7mcp",
                identifier="user_123",
                authorization_details=authorization_details,
            )
        ```

4. ### Authorize a user and make your first call

   **Node.js** (`quickstart.mts`)

   ```typescript
   import { ScalekitClient } from '@scalekit-sdk/node'
   import 'dotenv/config'
   import { createInterface } from 'node:readline/promises'

   const scalekit = new ScalekitClient(
     process.env.SCALEKIT_ENVIRONMENT_URL,
     process.env.SCALEKIT_CLIENT_ID,
     process.env.SCALEKIT_CLIENT_SECRET,
   )
   const actions = scalekit.actions

   const connector = 'context7mcp'
   const identifier = 'user_123'

   // Generate an authorization link for the user
   const { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })
   console.log('Authorize Context7 MCP:', link)
   const rl = createInterface({ input: process.stdin, output: process.stdout })
   await rl.question('Press Enter after authorizing...')
   rl.close()

   // Make your first call
   const result = await actions.executeTool({
     connector,
     identifier,
     toolName: 'context7mcp_query_docs',
     toolInput: { libraryId: '/mongodb/docs', query: 'YOUR_QUERY' },
   })
   console.log(result)
   ```

   ```bash
   npx tsx quickstart.mts
   ```

   **Python** (`quickstart.py`)

   ```python
   import os
   from scalekit import ScalekitClient
   from dotenv import load_dotenv
   load_dotenv()

   scalekit_client = ScalekitClient(
       env_url=os.getenv("SCALEKIT_ENVIRONMENT_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"

   # Generate an authorization link for the user
   link_response = actions.get_authorization_link(
       connection_name=connection_name,
       identifier=identifier,
   )
   print("Authorize Context7 MCP:", link_response.link)
   input("Press Enter after authorizing...")

   # Make your first call
   result = actions.execute_tool(
       tool_input={"libraryId":"/mongodb/docs","query":"YOUR_QUERY"},
       tool_name="context7mcp_query_docs",
       connection_name=connection_name,
       identifier=identifier,
   )
   print(result)
   ```

   ```bash
   python quickstart.py
   ```

   Each user opens the link once and enters their Context7 MCP server credentials there. If your app already has a user's credentials, add the account from your backend instead, as the console steps above show. See [Authorize a user](/agentkit/tools/authorize/) for the full flow and statuses.

## Tools

Pass the exact name to `execute_tool`, with an input like each tool's example. To ask for a tool that's missing, use the [request form](https://scalekitsupport.portal.usepylon.com/forms/request-a-connector-tool).

**Node.js**

```typescript
const result = await actions.executeTool({
  toolName: 'context7mcp_query_docs',
  toolInput: {
    libraryId: '/mongodb/docs',
    query: '<query>',
  },
  connector: 'context7mcp',
  identifier: 'user_123',
})
```

**Python**

```python
result = actions.execute_tool(
    tool_name="context7mcp_query_docs",
    tool_input={
        "libraryId": "/mongodb/docs",
        "query": "<query>",
    },
    connection_name="context7mcp",
    identifier="user_123",
)
```

`result.data` is the app's response as JSON, and `result.execution_id` (`executionId` in Node.js) is the ID of the call.

### `context7mcp_query_docs`

Context7 Query Docs · Read-only

Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework.

You must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

Do not call this tool more than 3 times per question.

Read only: yes. Destructive: no. Idempotent (safe to retry): yes.

Inputs:

- `libraryId` (`string`, required): Exact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'.
- `query` (`string`, required): What to look up in the library's documentation, scoped to a single concept. Be specific and include relevant details, but keep each query to one topic — if the user's question spans multiple distinct concepts, make a separate call per concept instead of combining them, unless the question is about how the concepts interact. Good: 'How to set up authentication with JWT in Express.js' or 'React useEffect cleanup function examples'. Bad (too vague): 'auth' or 'hooks'. Bad (too broad): 'routing and auth and caching in Next.js'. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query.

Also accepts `schema_version` and `tool_version` to pin a version.

Example input: `{"libraryId":"/mongodb/docs","query":"<query>"}`

### `context7mcp_resolve_library_id`

Context7 Resolve Library ID · Read-only

Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.

You MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

Each result includes:
- Library ID: Context7-compatible identifier (format: /org/project)
- Name: Library or package name
- Description: Short summary
- Code Snippets: Number of available code examples
- Source Reputation: Authority indicator (High, Medium, Low, or Unknown)
- Benchmark Score: Quality indicator (100 is the highest score)
- Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version.

For best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case.

Selection Process:
1. Analyze the query to understand what library/package the user is looking for
2. Return the most relevant match based on:
- Name similarity to the query (exact matches prioritized)
- Description relevance to the query's intent
- Documentation coverage (prioritize libraries with higher Code Snippet counts)
- Source reputation (consider libraries with High or Medium reputation more authoritative)
- Benchmark Score: Quality indicator (100 is the highest score)

Response Format:
- Return the selected library ID in a clearly marked section
- Provide a brief explanation for why this library was chosen
- If multiple good matches exist, acknowledge this but proceed with the most relevant one
- If no good matches exist, clearly state this and suggest query refinements

For ambiguous queries, request clarification before proceeding with a best-guess match.

IMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.

Read only: yes. Destructive: no. Idempotent (safe to retry): yes.

Inputs:

- `libraryName` (`string`, required): Library name to search for and retrieve a Context7-compatible library ID. Use the official library name with proper punctuation — e.g., 'Next.js' instead of 'nextjs', 'Customer.io' instead of 'customerio', 'Three.js' instead of 'threejs'.
- `query` (`string`, required): What to look up in the library's documentation. This is used to rank library results by relevance to what the user is trying to accomplish. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query.

Also accepts `schema_version` and `tool_version` to pin a version.

Example input: `{"libraryName":"Next.js","query":"<query>"}`

## Related

Other AI connectors ([all 116](/agentkit/connectors/?category=ai)):

- [Chorus](/agentkit/connectors/chorus/): Scalekit connector, Username and password, 9 tools
- [Gong](/agentkit/connectors/gong/): Scalekit connector, OAuth, 49 tools
- [Jiminny](/agentkit/connectors/jiminny/): Scalekit connector, Access token, 27 tools


---

## More Scalekit documentation

| Resource | What it contains | When to use it |
|----------|-----------------|----------------|
| [/llms.txt](/llms.txt) | Structured index with routing hints per product area | Start here — find which documentation set covers your topic before loading full content |
| [/llms-full.txt](/llms-full.txt) | Complete documentation for all Scalekit products in one file | Use when you need exhaustive context across multiple products or when the topic spans several areas |
| [sitemap-0.xml](https://docs.scalekit.com/sitemap-0.xml) | Full URL list of every documentation page | Use to discover specific page URLs you can fetch for targeted, page-level answers |