"A server that reviews GitHub pull requests or provides diffs" matching MCP servers:

MCP server for DCI API enabling AI models to extract and analyze DCI jobs, components, and topics, with integrations for Google Drive, Jira, GitHub, and Red Hat support cases.

Enables management of Bitbucket Cloud pull requests through natural language, including creating, reviewing, approving, and commenting on PRs with automatic default reviewer support.

A template and demonstration project for building, testing, and deploying remote MCP servers using FastMCP and uv. It provides a foundational structure for creating MCP-compliant tools that can be hosted publicly and integrated with LLM agents.

A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.

A minimal MCP server template for learning NitroStack fundamentals, featuring a calculator module with tools, resources, and prompts.

Query PainSpotter to discover validated business opportunities and trending pain points mined from Reddit, Hacker News, and Product Hunt.

Enables querying git commit history to analyze when and why code changes happened, providing authorship context and diffs for specific modules.

An MCP server that lets Claude analyze your TradingView charts by reading the window and taking screenshots, with no write tools or trade execution.

An open-source MCP server for live Apple App Store competitor research, enabling AI agents to search apps, fetch metadata, compare competitors, and retrieve reviews and top charts as structured JSON.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

An MCP server that provides AI agents with ICP Triangulation Framework™ for scoring prospects across firmographics, behaviors, and growth signals, plus RFM analysis and pipeline health scoring, with optional HubSpot integration.

A minimal MCP server that enables HTTP requests with any method, headers, and body types, supporting large responses through chunked transfers with disk-backed caching.

Enables AI agents and assistants to extract data from social media, search engines, maps, e-commerce sites, and any other website by running thousands of ready-made scrapers, crawlers, and automation tools as callable tools, with OAuth-based connection and optional agentic payments.

Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.

Use 3,000+ pre-built cloud tools from Apify, known as Actors, to extract data from websites, e-commerce, social media, search engines, maps, and more

Enables management of Kylas CRM lead operations, including creating leads, searching and filtering records, and resolving user, product, or pipeline IDs. It provides specialized tools for monitoring idle leads and accessing lead schema instructions through natural language.

Exposes network-monitoring tools (query metrics, analyze windows, compare, logs, status, runbooks, speed tests) as an MCP server for agentic workflows. Designed with evaluation suites, cost-aware model routing, and semantic tool retrieval.

Enables interaction with the CEDAR metadata repository, including fetching templates, searching BioPortal ontology terms, and managing template instances.

Revenue intelligence MCP server: RFM analysis, 14.5-point ICP scoring, pipeline health scoring. Embeds Artefact Formula methodology. HubSpot integration.

Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.