Lambda Capture MCP Server

What is Lambda Capture MCP Server?

A lightweight MCP server exposing a semantic‑search API for macroeconomic data. It lets large language models, AI agents, and quantitative research pipelines query economic indicators using natural‑language prompts and receive ranked results.

How to use Lambda Capture MCP Server?

Remote (HTTP) usage – Send a JSON‑RPC request to https://mcp.lambda-capture.com/v1/mcp/ with the method tools/call and the tool name macroecon_semantic_search. Example with 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}
    }
  }'

Local deployment – Clone the repository, install dependencies (Node 18+ or Python 3.11+), build the project, then run the server (npm run build && node dist/index.js for Node or python main.py for Python). Set the environment variable LAMBDA_CAPTURE_API_KEY with your Lambda Capture API key.

Key Features

• JSON‑RPC over HTTP with optional Server‑Sent Events streaming.
• Semantic search across curated macroeconomic datasets.
• Configurable result limit (max_results).
• Compatible with OpenAI tool calls and Claude Desktop MCP client.
• Supports both Node.js and Python implementations.

Use Cases

• Quantitative analysts querying recent inflation, GDP, or employment data without crafting SQL.
• Autonomous research agents that need up‑to‑date macro signals to adjust trading strategies.
• LLM‑driven chatbots providing economic insights in natural language.
• Academic projects requiring fast retrieval of macro indicators for modeling.

FAQ

Q: Do I need a Lambda Capture account? A: Yes, an API key is required for both remote and local instances.

Q: Which models are supported? A: Any model that can issue tool calls via the OpenAI or Claude MCP interfaces (e.g., GPT‑4.1, Claude).

Q: How many results can I request? A: The max_results parameter caps the returned hits; typical limits range from 1‑10.

Q: Can I run the server on my own infrastructure? A: Absolutely – the repository provides both Node and Python entry points for self‑hosting.

Q: Is the API rate‑limited? A: Rate limits are enforced on the Lambda Capture side; refer to your plan details for specifics.

Lambda Capture MCP Server

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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