"Using ast-grep to Modify Code Programmatically" matching MCP servers:

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.

Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.

Exposes 26 structured analytical tools over Climate Finance Update datasets, enabling fund-level financial analysis, portfolio aggregations, and data quality diagnostics without requiring the client to write data access code.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Provides tools to search and execute Code Ocean capsules and pipelines while managing platform data assets. It enables users to interact with Code Ocean's computational resources and scientific workflows directly through natural language interfaces.

Enables MCP clients to fetch live football odds and team form, and flag matches where the market price diverges from a simple form-based estimate.

Enables AI clients to query ContentRadar data and write low-risk content using natural language, with 15 tools for monitoring, analysis, and content management.

Enables searching and retrieving UK research grants, award values, institutions, and publications from the UKRI Gateway to Research API without authentication.

Provides tools to interact with the OpenCTI platform, including checking if a campaign exists.

Enables searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.

Enables searching and reading of AI/ML papers from conference proceedings and arxiv, with tools for full-text search, table of contents, and content grep.

Enables offline local LLM analysis of text data via MCP, taking raw text and an instruction to return analysis results without cloud calls.

Enables AI assistants to search arXiv's research repository, download papers, and access their content programmatically. Includes specialized prompts for comprehensive academic paper analysis covering methodology, results, and implications.

An MCP server for programmatically editing Jupyter notebooks, offering 29 tools for reading, modifying, and batch-processing notebooks without requiring a Jupyter server.

Provides CLI and MCP server to programmatically access Google NotebookLM, enabling AI assistants to create notebooks, add sources, generate podcasts, and more, with support for both personal and enterprise accounts.

Enables AI assistants to programmatically interact with Google NotebookLM, allowing them to create and manage notebooks, add sources, query content, generate audio/video, and perform research tasks through natural language commands.

Enables AI assistants to programmatically create, read, validate, and modify Stella system dynamics models in the XMILE format. It supports building complex stock-and-flow diagrams and exporting them as .stmx files for use in Stella Professional.

MCP server for Kaggle API integration that allows creating, running, and managing Kaggle notebooks programmatically.

Enables LLMs to load, simulate, modify, and generate what-if scenarios for EPANET water-distribution network models through natural language, leveraging the ePyT Python Toolkit.