Lambda Capture Server

Remote MCP Server GET/POST API
MCP implementation of our standard Semantic Search API for Macroeconomic Data

Remote MCP Server (streamable HTTP)

Check server status HERE

OpenAI Responses API

from openai import OpenAI

client = OpenAI()

resp = client.responses.create(
    model="gpt-4.1",
    input="Key shifts in inflation expectations",
    tools=[
        {
            "type": "mcp",
            "server_label": "lambda-capture",
            "server_url": "https://mcp.lambda-capture.com/v1/mcp/",
            "headers": {
                "Authorization": "Bearer YOUR_ACCESS_TOKEN"
            }
        }
    ]
)

print(resp.output_text)

Curl

curl -X POST "https://mcp.lambda-capture.com/v1/mcp/" \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-d '{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "macroecon_semantic_search",
    "arguments": {
      "query_text": "inflation expectations",
      "max_results": 3
    }
  }
}'

curl -X POST "https://mcp.lambda-capture.com/v1/mcp/" \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-d '{
    "jsonrpc": "2.0",
    "id": "1",
    "method": "list_tools",
    "params": {}
}'

Configure your MCP Client (Claude Desktop App)

Go to Claude -> Settings -> Developer -> Edit Config. Add the following to your claude_desktop_config.json

Node:

{
  "mcpServers": {
    "lambda-capture-mcp": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.lambda-capture.com/v1/mcp/",
        "--header", "Authorization: Bearer YOUR_ACCESS_TOKEN"
      ],
      "description": "RemoteMCP with Lambda Capture Macroeconomic Data API"
    }
  }
}

Local MCP Server

Pre-requisites

• Lambda Capture API key
• for MCP Typescript: Node.js 18+ (includes npx and npm)
• for MCP Python: Python 3.11+

Installation

1. Clone the repo

Node:

2. npm install to install the dependencies
3. npm run build to build the project

Python:

2. python -m venv .venv create virtual environment
3. source .venv/bin/activate activate virtual environment
4. pip install -r requirements.txt install the dependencies

Configure your MCP Client (Claude Desktop App)

Go to Claude -> Settings -> Developer -> Edit Config. Add the following to your claude_desktop_config.json

Node:

{
  "mcpServers": {
    "lambda-capture-mcp": {
      "command": "node",
      "args": [
        "/Absolute Path to/mcp-server/dist/index.js"
      ],
      "env": {
        "LAMBDA_CAPTURE_API_KEY": "Your API Key string"
      },
      "description": "Runs the Node MCP with Lambda Capture Macroeconomic Data API"
    }
  }
}

Python:

{
  "mcpServers": {
    "lambda-capture-mcp": {
      "command": "/Absolute Path to/.venv/bin/python",
      "args": [
        "/Absolute Path to/mcp-server/main.py"
      ],
      "env": {
        "LAMBDA_CAPTURE_API_KEY": "Your API Key string"
      },
      "description": "Runs the Python MCP with Lambda Capture Macroeconomic Data API"
    }
  }
}

Context Window Size

Adjust maxTokens (.ts) or max_tokens (.py) variables, based on context window size of your model (doesn't count metadata, just content tokens)

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