Integrations

Engram works with any MCP-compatible client. Here’s how to connect the most common ones.

Claude Desktop

Add to your claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json


{
  "mcpServers": {
    "engram": {
      "url": "https://mcp.getengram.app/mcp",
      "headers": {
        "Authorization": "Bearer engram_sk_live_your_key_here"
      }
    }
  }
}

Restart Claude Desktop. Engram’s 6 tools will appear in Claude’s tool list.

Claude Code (CLI)

Add to your project’s .mcp.json or global config:


{
  "mcpServers": {
    "engram": {
      "type": "url",
      "url": "https://mcp.getengram.app/mcp",
      "headers": {
        "Authorization": "Bearer engram_sk_live_your_key_here"
      }
    }
  }
}

Cursor

In Cursor Settings > MCP, add a new server:

Name: engram
Type: HTTP
URL: https://mcp.getengram.app/mcp
Headers: Authorization: Bearer engram_sk_live_your_key_here

Windsurf

Add to your Windsurf MCP configuration:


{
  "mcpServers": {
    "engram": {
      "serverUrl": "https://mcp.getengram.app/mcp",
      "headers": {
        "Authorization": "Bearer engram_sk_live_your_key_here"
      }
    }
  }
}

Custom MCP Client (TypeScript)

Use the official @modelcontextprotocol/sdk:


import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";
 
const transport = new StreamableHTTPClientTransport(
  new URL("https://mcp.getengram.app/mcp"),
  {
    requestInit: {
      headers: {
        Authorization: "Bearer engram_sk_live_your_key_here",
      },
    },
  }
);
 
const client = new Client({ name: "my-agent", version: "1.0.0" });
await client.connect(transport);
 
// Create a conversation
const result = await client.callTool({
  name: "create_conversation",
  arguments: {
    title: "My first conversation",
    tags: ["test"],
  },
});
 
console.log(result);
// { content: [{ type: "text", text: '{"conversation_id":"conv_..."}' }] }

Custom MCP Client (Python)


from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
 
async def main():
    headers = {
        "Authorization": "Bearer engram_sk_live_your_key_here"
    }
 
    async with streamablehttp_client(
        "https://mcp.getengram.app/mcp",
        headers=headers
    ) as (read, write, _):
        async with ClientSession(read, write) as session:
            await session.initialize()
 
            result = await session.call_tool(
                "search",
                arguments={"query": "billing issue", "limit": 5}
            )
            print(result)

MCP Inspector

For testing and debugging, use the MCP Inspector:


npx @anthropic-ai/mcp-inspector

Enter your server URL (https://mcp.getengram.app/mcp) and API key. You can interactively call tools, inspect schemas, and see responses.

Using with AI Frameworks

LangChain / LangGraph

Engram works as an MCP tool provider. Use LangChain’s MCP integration to connect:


import { McpToolkit } from "@langchain/mcp";
 
const toolkit = new McpToolkit({
  servers: {
    engram: {
      url: "https://mcp.getengram.app/mcp",
      headers: {
        Authorization: "Bearer engram_sk_live_your_key_here",
      },
    },
  },
});
 
const tools = await toolkit.getTools();
// tools now contains create_conversation, append_messages, search, etc.

Vercel AI SDK

Use the MCP client adapter:


import { experimental_createMCPClient } from "ai";
 
const engram = await experimental_createMCPClient({
  transport: {
    type: "sse",
    url: "https://mcp.getengram.app/mcp",
    headers: {
      Authorization: "Bearer engram_sk_live_your_key_here",
    },
  },
});
 
const tools = await engram.tools();