Langgraph Deepsearch MCP Server

MCPサーバーがClaude DesktopなどのMCPホストに接続されると、以下のような自然言語でリサーチを依頼できます:

Local serverstdioPython

What is the Langgraph Deepsearch MCP MCP server?

Langgraph Deepsearch MCP MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. MCPサーバーがClaude DesktopなどのMCPホストに接続されると、以下のような自然言語でリサーチを依頼できます:.

What the assistant can call

Once Langgraph Deepsearch MCP is connected, these are the calls the assistant has available:

  • GEMINI_API_KEY — Gemini API (必須) - Google AI Studioから取得
  • deep_search — The deep_search tool exposed by this server
  • quick_search — The quick_search tool exposed by this server
  • get_search_tools — The get_search_tools tool exposed by this server

Configuration and credentials

You will need one environment variable: GEMINI_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

Setting it up

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.

Choosing this one

Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Langgraph Deepsearch MCP's toolset — GEMINI_API_KEY, deep_search, quick_search and 1 more — is a fair guide to whether it matches your workflow. It is maintained by RyotaOzawa0; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the langgraph deepsearch mcp mcp server does with a few real requests.

Available tools

ToolWhat it does
GEMINI_API_KEYGemini API (必須) - [Google AI Studio](https://aistudio.google.com/app/apikey)から取得
deep_searchThe deep_search tool exposed by this server.
quick_searchThe quick_search tool exposed by this server.
get_search_toolsThe get_search_tools tool exposed by this server.

How to install the Langgraph Deepsearch MCP MCP server

{
  "mcpServers": {
    "langgraph-deep-search": {
      "command": "uvx",
      "args": ["--from", "/path/to/deep-search-mcp-server", "langgraph-deep-search"],
      "env": {
        "GEMINI_API_KEY": "your_gemini_api_key"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

VariableDescriptionRequired
GEMINI_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use Langgraph Deepsearch MCP to GEMINI API KEY.
  • Use Langgraph Deepsearch MCP to deep search.
  • Use Langgraph Deepsearch MCP to quick search.

Frequently asked questions

It connects Langgraph Deepsearch MCP to MCP-compatible AI assistants such as Claude and Cursor, exposing 4 tools (GEMINI_API_KEY, deep_search, quick_search, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Langgraph Deepsearch MCP directly.