"Tools for Efficient Diff Editing, Patching, and File System Operations" matching MCP servers:

An MCP-native pipeline for collecting structured intelligence on higher education institutions using the WHED schema, enabling scraping, extraction, validation, and saving of profiles.

A production-quality multi-agent research system with an arXiv MCP server and LangGraph-based research agents, providing search, details, and cached summaries via SQLite.

MCP server for Jupyter notebook navigation and editing. Reads .ipynb files directly as JSON, providing efficient tools for reading, searching, and modifying cells without needing a Jupyter server.

Presents a plausible, tool-rich workspace surface — file reading, credential listing, command execution, database queries, and configuration retrieval — that returns only synthetic results while logging every connection, tool call, and argument received. It enables researchers to measure what MCP clients and agents actually do when handed dangerous-sounding tools, including whether they follow injected instructions or complete a retrieve-then-use credential chain.

Provides five rigorous reasoning protocols (debate, red team, audit_argument, threat_model, check_study) that run on the AI you're already using, requiring no extra API keys or costs.

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

Provides in-process RDKit cheminformatics operations — descriptors, fingerprints, similarity and substructure search, reaction enumeration, standardization, and 3D conformer generation — for AI agents.

Enables read-only analysis of local unstructured documents by scanning a folder, extracting text and structural metadata, and passing content with truncation and error-awareness to an LLM for summarization.

Provides actionable financial intelligence tools for AI agents including insider buying signals, earnings IV plays, market pulse, stock analysis, and options strategies via free public data sources.

An MCP server for managing pandoc/CSL-YAML bibliographies and verifying citations in documents.

Enables querying MITRE ATT&CK and D3FEND data efficiently, providing techniques, detections, mitigations, actors, and countermeasures with token-aware summaries and paginated graph traversal.

High-value scientific tools for AI agents — literature search (PubMed, arXiv, Semantic Scholar), chemical compound lookup (PubChem, ChEMBL), patent prior art search (USPTO, EPO), GPU spot prices across 4 providers, and real-time earth science data (USGS, NASA, OpenAQ). Per-call billing via API key. Keys issued instantly at https://mcp-site.com/keys/request

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

An MCP server that enables users to read, search, and analyze PDF documents. It provides tools for extracting text, viewing metadata, searching content with context, and generating word statistics.

Enables querying real-time adoption metrics, trends, and comparisons for popular AI coding tools like OpenAI SDK, Anthropic SDK, Cursor, GitHub Copilot, and LangChain through natural language.

An MCP server that provides comprehensive financial insights and analysis by leveraging real-time market data, news, and advanced analytics for stocks, options, financial statements, and economic indicators.

An MCP server for global tech intelligence gathering, offering tools for searching Chinese and English web content, GitHub trending, arXiv papers, HN, Exa, SEC filings, Juejin, Zhihu, Bilibili, and A-share financial reports, all without API keys and with direct China access.

Provides honest A/B test verdicts using interactive cards, with statistical calculations for conversion rates, sample sizes, and Bayesian probability-to-beat.

Enables AI-driven COMSOL batch jobs on the Harvard FASRC cluster, allowing users to run COMSOL models, manage jobs, and fetch results directly through natural language.

Enables any MCP-capable agent to call Kimi Code's official managed web search, URL fetch, and 25+ professional data sources (Wind, SEC EDGAR, S&P, World Bank, IMF, FRED, Tianyancha, arXiv, Scholar, Chinese law & standards, WHO/FAO/OECD, Xinhua, Caixin) through a zero-dependency stdio server. Each user signs in with their own paid Kimi account via OAuth device flow, and credentials are stored locally with tokens never exposed to agents.