# Source: https://platform.claude.com/docs/en/agent-sdk/mcp.md

# Connect to external tools with MCP

Configure MCP servers to extend your agent with external tools. Covers transport types, tool search for large tool sets, authentication, and error handling.

---

The [Model Context Protocol (MCP)](https://modelcontextprotocol.io/docs/getting-started/intro) is an open standard for connecting AI agents to external tools and data sources. With MCP, your agent can query databases, integrate with APIs like Slack and GitHub, and connect to other services without writing custom tool implementations.

MCP servers can run as local processes, connect over HTTP, or execute directly within your SDK application.

## Quickstart

This example connects to the [Claude Code documentation](https://code.claude.com/docs) MCP server using [HTTP transport](#httpsse-servers) and uses [`allowedTools`](#allow-mcp-tools) with a wildcard to permit all tools from the server.

<CodeGroup>

```typescript TypeScript
import { query } from "@anthropic-ai/claude-agent-sdk";

for await (const message of query({
  prompt: "Use the docs MCP server to explain what hooks are in Claude Code",
  options: {
    mcpServers: {
      "claude-code-docs": {
        type: "http",
        url: "https://code.claude.com/docs/mcp"
      }
    },
    allowedTools: ["mcp__claude-code-docs__*"]
  }
})) {
  if (message.type === "result" && message.subtype === "success") {
    console.log(message.result);
  }
}
```

```python Python
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage

async def main():
    options = ClaudeAgentOptions(
        mcp_servers={
            "claude-code-docs": {
                "type": "http",
                "url": "https://code.claude.com/docs/mcp"
            }
        },
        allowed_tools=["mcp__claude-code-docs__*"]
    )

    async for message in query(prompt="Use the docs MCP server to explain what hooks are in Claude Code", options=options):
        if isinstance(message, ResultMessage) and message.subtype == "success":
            print(message.result)

asyncio.run(main())
```

</CodeGroup>

The agent connects to the documentation server, searches for information about hooks, and returns the results.

## Add an MCP server

You can configure MCP servers in code when calling `query()`, or in a `.mcp.json` file that the SDK loads automatically.

### In code

Pass MCP servers directly in the `mcpServers` option:

<CodeGroup>

```typescript TypeScript
import { query } from "@anthropic-ai/claude-agent-sdk";

for await (const message of query({
  prompt: "List files in my project",
  options: {
    mcpServers: {
      "filesystem": {
        command: "npx",
        args: ["-y", "@modelcontextprotocol/server-filesystem", "/Users/me/projects"]
      }
    },
    allowedTools: ["mcp__filesystem__*"]
  }
})) {
  if (message.type === "result" && message.subtype === "success") {
    console.log(message.result);
  }
}
```

```python Python
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage

async def main():
    options = ClaudeAgentOptions(
        mcp_servers={
            "filesystem": {
                "command": "npx",
                "args": ["-y", "@modelcontextprotocol/server-filesystem", "/Users/me/projects"]
            }
        },
        allowed_tools=["mcp__filesystem__*"]
    )

    async for message in query(prompt="List files in my project", options=options):
        if isinstance(message, ResultMessage) and message.subtype == "success":
            print(message.result)

asyncio.run(main())
```

</CodeGroup>

### From a config file

Create a `.mcp.json` file at your project root. The SDK loads this automatically:

```json
{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/Users/me/projects"]
    }
  }
}
```

## Allow MCP tools

MCP tools require explicit permission before Claude can use them. Without permission, Claude will see that tools are available but won't be able to call them.

### Tool naming convention

MCP tools follow the naming pattern `mcp__<server-name>__<tool-name>`. For example, a GitHub server named `"github"` with a `list_issues` tool becomes `mcp__github__list_issues`.

### Grant access with allowedTools

Use `allowedTools` to specify which MCP tools Claude can use:

```typescript
options: {
  mcpServers: { /* your servers */ },
  allowedTools: [
    "mcp__github__*",              // All tools from the github server
    "mcp__db__query",              // Only the query tool from db server
    "mcp__slack__send_message"     // Only send_message from slack server
  ]
}
```

Wildcards (`*`) let you allow all tools from a server without listing each one individually.

### Alternative: Change the permission mode

Instead of listing allowed tools, you can change the permission mode to grant broader access:

- `permissionMode: "acceptEdits"`: Automatically approves tool usage (still prompts for destructive operations)
- `permissionMode: "bypassPermissions"`: Skips all safety prompts, including for destructive operations like file deletion or running shell commands. Use with caution, especially in production. This mode propagates to subagents spawned by the Task tool.

```typescript
options: {
  mcpServers: { /* your servers */ },
  permissionMode: "acceptEdits"  // No need for allowedTools
}
```

See [Permissions](/docs/en/agent-sdk/permissions) for more details on permission modes.

### Discover available tools

To see what tools an MCP server provides, check the server's documentation or connect to the server and inspect the `system` init message:

```typescript
for await (const message of query({ prompt: "...", options })) {
  if (message.type === "system" && message.subtype === "init") {
    console.log("Available MCP tools:", message.mcp_servers);
  }
}
```

## Transport types

MCP servers communicate with your agent using different transport protocols. Check the server's documentation to see which transport it supports:

- If the docs give you a **command to run** (like `npx @modelcontextprotocol/server-github`), use stdio
- If the docs give you a **URL**, use HTTP or SSE
- If you're building your own tools in code, use an SDK MCP server

### stdio servers

Local processes that communicate via stdin/stdout. Use this for MCP servers you run on the same machine:

<Tabs>
  <Tab title="In code">
    <CodeGroup>

    ```typescript TypeScript
    options: {
      mcpServers: {
        "github": {
          command: "npx",
          args: ["-y", "@modelcontextprotocol/server-github"],
          env: {
            GITHUB_TOKEN: process.env.GITHUB_TOKEN
          }
        }
      },
      allowedTools: ["mcp__github__list_issues", "mcp__github__search_issues"]
    }
    ```

    ```python Python
    options = ClaudeAgentOptions(
        mcp_servers={
            "github": {
                "command": "npx",
                "args": ["-y", "@modelcontextprotocol/server-github"],
                "env": {
                    "GITHUB_TOKEN": os.environ["GITHUB_TOKEN"]
                }
            }
        },
        allowed_tools=["mcp__github__list_issues", "mcp__github__search_issues"]
    )
    ```

    </CodeGroup>
  </Tab>
  <Tab title=".mcp.json">
    ```json
    {
      "mcpServers": {
        "github": {
          "command": "npx",
          "args": ["-y", "@modelcontextprotocol/server-github"],
          "env": {
            "GITHUB_TOKEN": "${GITHUB_TOKEN}"
          }
        }
      }
    }
    ```
  </Tab>
</Tabs>

### HTTP/SSE servers

Use HTTP or SSE for cloud-hosted MCP servers and remote APIs:

<Tabs>
  <Tab title="In code">
    <CodeGroup>

    ```typescript TypeScript
    options: {
      mcpServers: {
        "remote-api": {
          type: "sse",
          url: "https://api.example.com/mcp/sse",
          headers: {
            Authorization: `Bearer ${process.env.API_TOKEN}`
          }
        }
      },
      allowedTools: ["mcp__remote-api__*"]
    }
    ```

    ```python Python
    options = ClaudeAgentOptions(
        mcp_servers={
            "remote-api": {
                "type": "sse",
                "url": "https://api.example.com/mcp/sse",
                "headers": {
                    "Authorization": f"Bearer {os.environ['API_TOKEN']}"
                }
            }
        },
        allowed_tools=["mcp__remote-api__*"]
    )
    ```

    </CodeGroup>
  </Tab>
  <Tab title=".mcp.json">
    ```json
    {
      "mcpServers": {
        "remote-api": {
          "type": "sse",
          "url": "https://api.example.com/mcp/sse",
          "headers": {
            "Authorization": "Bearer ${API_TOKEN}"
          }
        }
      }
    }
    ```
  </Tab>
</Tabs>

For HTTP (non-streaming), use `"type": "http"` instead.

### SDK MCP servers

Define custom tools directly in your application code instead of running a separate server process. See the [custom tools guide](/docs/en/agent-sdk/custom-tools) for implementation details.

## MCP tool search

When you have many MCP tools configured, tool definitions can consume a significant portion of your context window. MCP tool search solves this by dynamically loading tools on-demand instead of preloading all of them.

### How it works

Tool search runs in auto mode by default. It activates when your MCP tool descriptions would consume more than 10% of the context window. When triggered:

1. MCP tools are marked with `defer_loading: true` rather than loaded into context upfront
2. Claude uses a search tool to discover relevant MCP tools when needed
3. Only the tools Claude actually needs are loaded into context

Tool search requires models that support `tool_reference` blocks: Sonnet 4 and later, or Opus 4 and later. Haiku models do not support tool search.

### Configure tool search

Control tool search behavior with the `ENABLE_TOOL_SEARCH` environment variable:

| Value | Behavior |
|:------|:---------|
| `auto` | Activates when MCP tools exceed 10% of context (default) |
| `auto:5` | Activates at 5% threshold (customize the percentage) |
| `true` | Always enabled |
| `false` | Disabled, all MCP tools loaded upfront |

Set the value in the `env` option:

<CodeGroup>

```typescript TypeScript
const options = {
  mcpServers: { /* your MCP servers */ },
  env: {
    ENABLE_TOOL_SEARCH: "auto:5"  // Enable at 5% threshold
  }
};
```

```python Python
options = ClaudeAgentOptions(
    mcp_servers={ ... },  # your MCP servers
    env={
        "ENABLE_TOOL_SEARCH": "auto:5"  # Enable at 5% threshold
    }
)
```

</CodeGroup>

## Authentication

Most MCP servers require authentication to access external services. Pass credentials through environment variables in the server configuration.

### Pass credentials via environment variables

Use the `env` field to pass API keys, tokens, and other credentials to the MCP server:

<Tabs>
  <Tab title="In code">
    <CodeGroup>

    ```typescript TypeScript
    options: {
      mcpServers: {
        "github": {
          command: "npx",
          args: ["-y", "@modelcontextprotocol/server-github"],
          env: {
            GITHUB_TOKEN: process.env.GITHUB_TOKEN
          }
        }
      },
      allowedTools: ["mcp__github__list_issues"]
    }
    ```

    ```python Python
    options = ClaudeAgentOptions(
        mcp_servers={
            "github": {
                "command": "npx",
                "args": ["-y", "@modelcontextprotocol/server-github"],
                "env": {
                    "GITHUB_TOKEN": os.environ["GITHUB_TOKEN"]
                }
            }
        },
        allowed_tools=["mcp__github__list_issues"]
    )
    ```

    </CodeGroup>
  </Tab>
  <Tab title=".mcp.json">
    ```json
    {
      "mcpServers": {
        "github": {
          "command": "npx",
          "args": ["-y", "@modelcontextprotocol/server-github"],
          "env": {
            "GITHUB_TOKEN": "${GITHUB_TOKEN}"
          }
        }
      }
    }
    ```

    The `${GITHUB_TOKEN}` syntax expands environment variables at runtime.
  </Tab>
</Tabs>

See [List issues from a repository](#list-issues-from-a-repository) for a complete working example with debug logging.

### HTTP headers for remote servers

For HTTP and SSE servers, pass authentication headers directly in the server configuration:

<Tabs>
  <Tab title="In code">
    <CodeGroup>

    ```typescript TypeScript
    options: {
      mcpServers: {
        "secure-api": {
          type: "http",
          url: "https://api.example.com/mcp",
          headers: {
            Authorization: `Bearer ${process.env.API_TOKEN}`
          }
        }
      },
      allowedTools: ["mcp__secure-api__*"]
    }
    ```

    ```python Python
    options = ClaudeAgentOptions(
        mcp_servers={
            "secure-api": {
                "type": "http",
                "url": "https://api.example.com/mcp",
                "headers": {
                    "Authorization": f"Bearer {os.environ['API_TOKEN']}"
                }
            }
        },
        allowed_tools=["mcp__secure-api__*"]
    )
    ```

    </CodeGroup>
  </Tab>
  <Tab title=".mcp.json">
    ```json
    {
      "mcpServers": {
        "secure-api": {
          "type": "http",
          "url": "https://api.example.com/mcp",
          "headers": {
            "Authorization": "Bearer ${API_TOKEN}"
          }
        }
      }
    }
    ```

    The `${API_TOKEN}` syntax expands environment variables at runtime.
  </Tab>
</Tabs>

### OAuth2 authentication

The [MCP specification supports OAuth 2.1](https://modelcontextprotocol.io/specification/2025-03-26/basic/authorization) for authorization. The SDK doesn't handle OAuth flows automatically, but you can pass access tokens via headers after completing the OAuth flow in your application:

<CodeGroup>

```typescript TypeScript
// After completing OAuth flow in your app
const accessToken = await getAccessTokenFromOAuthFlow();

const options = {
  mcpServers: {
    "oauth-api": {
      type: "http",
      url: "https://api.example.com/mcp",
      headers: {
        Authorization: `Bearer ${accessToken}`
      }
    }
  },
  allowedTools: ["mcp__oauth-api__*"]
};
```

```python Python
# After completing OAuth flow in your app
access_token = await get_access_token_from_oauth_flow()

options = ClaudeAgentOptions(
    mcp_servers={
        "oauth-api": {
            "type": "http",
            "url": "https://api.example.com/mcp",
            "headers": {
                "Authorization": f"Bearer {access_token}"
            }
        }
    },
    allowed_tools=["mcp__oauth-api__*"]
)
```

</CodeGroup>

## Examples

### List issues from a repository

This example connects to the [GitHub MCP server](https://github.com/modelcontextprotocol/servers/tree/main/src/github) to list recent issues. The example includes debug logging to verify the MCP connection and tool calls.

Before running, create a [GitHub personal access token](https://github.com/settings/tokens) with `repo` scope and set it as an environment variable:

```bash
export GITHUB_TOKEN=ghp_xxxxxxxxxxxxxxxxxxxx
```

<CodeGroup>

```typescript TypeScript
import { query } from "@anthropic-ai/claude-agent-sdk";

for await (const message of query({
  prompt: "List the 3 most recent issues in anthropics/claude-code",
  options: {
    mcpServers: {
      "github": {
        command: "npx",
        args: ["-y", "@modelcontextprotocol/server-github"],
        env: {
          GITHUB_TOKEN: process.env.GITHUB_TOKEN
        }
      }
    },
    allowedTools: ["mcp__github__list_issues"]
  }
})) {
  // Verify MCP server connected successfully
  if (message.type === "system" && message.subtype === "init") {
    console.log("MCP servers:", message.mcp_servers);
  }

  // Log when Claude calls an MCP tool
  if (message.type === "assistant") {
    for (const block of message.content) {
      if (block.type === "tool_use" && block.name.startsWith("mcp__")) {
        console.log("MCP tool called:", block.name);
      }
    }
  }

  // Print the final result
  if (message.type === "result" && message.subtype === "success") {
    console.log(message.result);
  }
}
```

```python Python
import asyncio
import os
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage, SystemMessage, AssistantMessage

async def main():
    options = ClaudeAgentOptions(
        mcp_servers={
            "github": {
                "command": "npx",
                "args": ["-y", "@modelcontextprotocol/server-github"],
                "env": {
                    "GITHUB_TOKEN": os.environ["GITHUB_TOKEN"]
                }
            }
        },
        allowed_tools=["mcp__github__list_issues"]
    )

    async for message in query(prompt="List the 3 most recent issues in anthropics/claude-code", options=options):
        # Verify MCP server connected successfully
        if isinstance(message, SystemMessage) and message.subtype == "init":
            print("MCP servers:", message.data.get("mcp_servers"))

        # Log when Claude calls an MCP tool
        if isinstance(message, AssistantMessage):
            for block in message.content:
                if hasattr(block, "name") and block.name.startswith("mcp__"):
                    print("MCP tool called:", block.name)

        # Print the final result
        if isinstance(message, ResultMessage) and message.subtype == "success":
            print(message.result)

asyncio.run(main())
```

</CodeGroup>

### Query a database

This example uses the [Postgres MCP server](https://github.com/modelcontextprotocol/servers/tree/main/src/postgres) to query a database. The connection string is passed as an argument to the server. The agent automatically discovers the database schema, writes the SQL query, and returns the results:

<CodeGroup>

```typescript TypeScript
import { query } from "@anthropic-ai/claude-agent-sdk";

// Connection string from environment variable
const connectionString = process.env.DATABASE_URL;

for await (const message of query({
  // Natural language query - Claude writes the SQL
  prompt: "How many users signed up last week? Break it down by day.",
  options: {
    mcpServers: {
      "postgres": {
        command: "npx",
        // Pass connection string as argument to the server
        args: ["-y", "@modelcontextprotocol/server-postgres", connectionString]
      }
    },
    // Allow only read queries, not writes
    allowedTools: ["mcp__postgres__query"]
  }
})) {
  if (message.type === "result" && message.subtype === "success") {
    console.log(message.result);
  }
}
```

```python Python
import asyncio
import os
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage

async def main():
    # Connection string from environment variable
    connection_string = os.environ["DATABASE_URL"]

    options = ClaudeAgentOptions(
        mcp_servers={
            "postgres": {
                "command": "npx",
                # Pass connection string as argument to the server
                "args": ["-y", "@modelcontextprotocol/server-postgres", connection_string]
            }
        },
        # Allow only read queries, not writes
        allowed_tools=["mcp__postgres__query"]
    )

    # Natural language query - Claude writes the SQL
    async for message in query(
        prompt="How many users signed up last week? Break it down by day.",
        options=options
    ):
        if isinstance(message, ResultMessage) and message.subtype == "success":
            print(message.result)

asyncio.run(main())
```

</CodeGroup>

## Error handling

MCP servers can fail to connect for various reasons: the server process might not be installed, credentials might be invalid, or a remote server might be unreachable.

The SDK emits a `system` message with subtype `init` at the start of each query. This message includes the connection status for each MCP server. Check the `status` field to detect connection failures before the agent starts working:

<CodeGroup>

```typescript TypeScript
import { query } from "@anthropic-ai/claude-agent-sdk";

for await (const message of query({
  prompt: "Process data",
  options: {
    mcpServers: {
      "data-processor": dataServer
    }
  }
})) {
  if (message.type === "system" && message.subtype === "init") {
    const failedServers = message.mcp_servers.filter(
      s => s.status !== "connected"
    );

    if (failedServers.length > 0) {
      console.warn("Failed to connect:", failedServers);
    }
  }

  if (message.type === "result" && message.subtype === "error_during_execution") {
    console.error("Execution failed");
  }
}
```

```python Python
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, SystemMessage, ResultMessage

async def main():
    options = ClaudeAgentOptions(
        mcp_servers={
            "data-processor": data_server
        }
    )

    async for message in query(prompt="Process data", options=options):
        if isinstance(message, SystemMessage) and message.subtype == "init":
            failed_servers = [
                s for s in message.data.get("mcp_servers", [])
                if s.get("status") != "connected"
            ]

            if failed_servers:
                print(f"Failed to connect: {failed_servers}")

        if isinstance(message, ResultMessage) and message.subtype == "error_during_execution":
            print("Execution failed")

asyncio.run(main())
```

</CodeGroup>

## Troubleshooting

### Server shows "failed" status

Check the `init` message to see which servers failed to connect:

```typescript
if (message.type === "system" && message.subtype === "init") {
  for (const server of message.mcp_servers) {
    if (server.status === "failed") {
      console.error(`Server ${server.name} failed to connect`);
    }
  }
}
```

Common causes:

- **Missing environment variables**: Ensure required tokens and credentials are set. For stdio servers, check the `env` field matches what the server expects.
- **Server not installed**: For `npx` commands, verify the package exists and Node.js is in your PATH.
- **Invalid connection string**: For database servers, verify the connection string format and that the database is accessible.
- **Network issues**: For remote HTTP/SSE servers, check the URL is reachable and any firewalls allow the connection.

### Tools not being called

If Claude sees tools but doesn't use them, check that you've granted permission with `allowedTools` or by [changing the permission mode](#alternative-change-the-permission-mode):

```typescript
options: {
  mcpServers: { /* your servers */ },
  allowedTools: ["mcp__servername__*"]  // Required for Claude to use the tools
}
```

### Connection timeouts

The MCP SDK has a default timeout of 60 seconds for server connections. If your server takes longer to start, the connection will fail. For servers that need more startup time, consider:

- Using a lighter-weight server if available
- Pre-warming the server before starting your agent
- Checking server logs for slow initialization causes

## Related resources

- **[Custom tools guide](/docs/en/agent-sdk/custom-tools)**: Build your own MCP server that runs in-process with your SDK application
- **[Permissions](/docs/en/agent-sdk/permissions)**: Control which MCP tools your agent can use with `allowedTools` and `disallowedTools`
- **[TypeScript SDK reference](/docs/en/agent-sdk/typescript)**: Full API reference including MCP configuration options
- **[Python SDK reference](/docs/en/agent-sdk/python)**: Full API reference including MCP configuration options
- **[MCP server directory](https://github.com/modelcontextprotocol/servers)**: Browse available MCP servers for databases, APIs, and more