io.github.capyBearista/gemini-researcher MCP Server

io.github.capyBearista/gemini-researcher

Repository Registry

What is the io.github.capyBearista/gemini-researcher MCP server?

Stateless MCP server that proxies research queries to Gemini CLI, reducing agent context/model usage

How to install io.github.capyBearista/gemini-researcher

Copy-paste configuration for popular MCP clients.

transport: stdio

Config generated by PluginBench — verify against the source before use.

Environment / auth

GEMINI_API_KEY
secret
Gemini API key (optional if you already authenticated Gemini CLI via "gemini" login)
PROJECT_ROOT
Override the project root directory used for path validation (defaults to current working directory)
RESPONSE_CHUNK_SIZE_KB
Chunk size threshold (KB) for large responses (default: 10)
CACHE_TTL_MS
Chunk cache TTL in milliseconds (default: 3600000 / 1 hour)
DEBUG
Enable debug logging (set to "true" or "1")
GOOGLE_APPLICATION_CREDENTIALS
Vertex AI / Google auth: path to a service account JSON credentials file
GOOGLE_CLOUD_PROJECT
Vertex AI / Google auth: GCP project ID (used by some auth configurations)
VERTEX_AI_PROJECT
Vertex AI / Google auth: Vertex AI project identifier (used by some auth configurations)

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "gemini-researcher": {
      "command": "npx",
      "args": [
        "-y",
        "gemini-researcher"
      ],
      "env": {
        "GEMINI_API_KEY": "<YOUR_GEMINI_API_KEY>",
        "PROJECT_ROOT": "<YOUR_PROJECT_ROOT>",
        "RESPONSE_CHUNK_SIZE_KB": "<YOUR_RESPONSE_CHUNK_SIZE_KB>",
        "CACHE_TTL_MS": "<YOUR_CACHE_TTL_MS>",
        "DEBUG": "<YOUR_DEBUG>",
        "GOOGLE_APPLICATION_CREDENTIALS": "<YOUR_GOOGLE_APPLICATION_CREDENTIALS>",
        "GOOGLE_CLOUD_PROJECT": "<YOUR_GOOGLE_CLOUD_PROJECT>",
        "VERTEX_AI_PROJECT": "<YOUR_VERTEX_AI_PROJECT>"
      }
    }
  }
}

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