Skip to main content

A MCP server project

Project description

gpt-researcher-mcp MCP server

A MCP server project

Components

Resources

The server implements a simple note storage system with:

  • Custom note:// URI scheme for accessing individual notes
  • Each note resource has a name, description and text/plain mimetype

Prompts

The server provides a single prompt:

  • summarize-notes: Creates summaries of all stored notes
    • Optional "style" argument to control detail level (brief/detailed)
    • Generates prompt combining all current notes with style preference

Tools

The server implements one tool:

  • add-note: Adds a new note to the server
    • Takes "name" and "content" as required string arguments
    • Updates server state and notifies clients of resource changes

Configuration

[TODO: Add configuration details specific to your implementation]

Quickstart

Install

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

Development/Unpublished Servers Configuration ``` "mcpServers": { "gpt-researcher-mcp": { "command": "uv", "args": [ "--directory", "/home/markchiang/projects/gpt-researcher-mcp", "run", "gpt-researcher-mcp" ] } } ```
Published Servers Configuration ``` "mcpServers": { "gpt-researcher-mcp": { "command": "uvx", "args": [ "gpt-researcher-mcp" ] } } ```

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

  • Token: --token or UV_PUBLISH_TOKEN
  • Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory /home/markchiang/projects/gpt-researcher-mcp run gpt-researcher-mcp

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gpt_researcher_mcp-0.1.2.tar.gz (155.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gpt_researcher_mcp-0.1.2-py3-none-any.whl (5.8 kB view details)

Uploaded Python 3

File details

Details for the file gpt_researcher_mcp-0.1.2.tar.gz.

File metadata

  • Download URL: gpt_researcher_mcp-0.1.2.tar.gz
  • Upload date:
  • Size: 155.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.11

File hashes

Hashes for gpt_researcher_mcp-0.1.2.tar.gz
Algorithm Hash digest
SHA256 4e5d51a76783373fb00bd0530d4c276b587199fbfca4b8fc81235249ee770f2b
MD5 3f61ad072f200ba632c9ddc57af7929f
BLAKE2b-256 96f717de273e9c2404d5d9f7f9056cd9d548433e8dd2d6adfc97406ef0811980

See more details on using hashes here.

File details

Details for the file gpt_researcher_mcp-0.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for gpt_researcher_mcp-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 18a817769674fed0ba551ee6e9a92d10e525bd79d8bba6e83c539ba73997cb43
MD5 c9a97725a303cdab8af54c53707d3054
BLAKE2b-256 2e48fa7c860508d928864f827fa89550d61959ed96ace7b4665fa8666e6b946e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page