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Documentation Index

Fetch the complete documentation index at: https://docs.footstep.ai/llms.txt

Use this file to discover all available pages before exploring further.

Connect to the hosted server at mcp.footstep.ai. No installation, no Node.js required.

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Claude Desktop

Add to your claude_desktop_config.json (Settings > Developer > Edit Config): 
{
  "mcpServers": {
    "footstep": {
      "url": "https://mcp.footstep.ai",
      "headers": {
        "x-api-key": "sk_live_your_key_here"
      }
    }
  }
}

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Cursor / Claude Code / Cline

Add to your project’s .mcp.json (or the equivalent MCP config for your client): 
{
  "mcpServers": {
    "footstep": {
      "url": "https://mcp.footstep.ai",
      "headers": {
        "x-api-key": "sk_live_your_key_here"
      }
    }
  }
}

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OpenAI Agents SDK

from agents import Agent
from agents.mcp import MCPServerStreamableHttp

footstep = MCPServerStreamableHttp(
    url="https://mcp.footstep.ai",
    headers={"x-api-key": "sk_live_your_key_here"},
)

agent = Agent(
    name="travel-agent",
    instructions="You help plan routes and find locations.",
    mcp_servers=[footstep],
)

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Google Gemini (via LangChain)

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_google_genai import ChatGoogleGenerativeAI
from langgraph.prebuilt import create_react_agent

client = MultiServerMCPClient({
    "footstep": {
        "url": "https://mcp.footstep.ai",
        "headers": {"x-api-key": "sk_live_your_key_here"},
        "transport": "streamable_http",
    }
})

tools = await client.get_tools()
model = ChatGoogleGenerativeAI(model="gemini-2.0-flash")
agent = create_react_agent(model, tools)

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Vercel AI SDK

import { experimental_createMCPClient as createMCPClient } from "ai";

const client = await createMCPClient({
  transport: {
    type: "http",
    url: "https://mcp.footstep.ai",
    headers: { "x-api-key": "sk_live_your_key_here" },
  },
});

const tools = await client.tools();
// Pass tools to any model: OpenAI, Anthropic, Google, etc.

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Custom agents

Any MCP client that supports Streamable HTTP transport can connect. Point it at https://mcp.footstep.ai and pass your API key in the x-api-key header.
The MCP server also accepts the standard Authorization: Bearer <key> form, so MCP SDKs that default to Bearer authentication work without configuration changes. x-api-key remains the recommended header.

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Reading responses

Tool results are returned in the MCP structuredContent field as parsed JSON — no JSON.parse step required. See response shape for the full envelope and the error code reference.

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Tuning what you get back

Every renderer-aware tool defaults to rich responses — geometry, render-ready GeoJSON layers, and full result sets are all included. Token-conscious LLM agents pass compact: true to suppress geometry and render envelopes; renderer-aware clients keep the defaults. See response defaults & controls.