"MCP servers for curated context in Cursor IDE to plan, debug, and iterate on features" matching MCP servers:

A workshop repository teaching advanced Model Context Protocol features for building AI-connected apps with deeper integration capabilities.

Provides Dev Container Features that install code intelligence (LSP) and repository knowledge search (Orama) MCP servers into any dev container, enabling coding agents to perform go-to-definition, find references, and hybrid search over project files.

MCP server that brings Trustabl static reliability scanning into Cursor, letting agents inventory agents/tools, flag risky patterns, score production readiness, and write SARIF reports.

An intelligent debugging assistant that automates the debugging process by analyzing bugs, injecting HTTP-based debug logs into code across multiple environments (browser, Node.js, mobile, etc.), and iteratively fixing issues based on real-time feedback.

Enables AI agents to access VS Code's LSP-based code navigation and native debugging tools (definitions, references, outline, breakpoints, stepping, stack frames, variables, and evaluate) via the MCP protocol.

A smart debugging agent that remembers errors, automatically diagnoses issues, and accumulates solutions for faster resolution.

A live post-mortem debugger MCP server for Home Assistant that lets AI agents list captured exceptions, walk traceback frames, read local variables, and optionally evaluate Python in the context of a captured frame for true post-mortem debugging.

A local MCP server that improves token efficiency for Cursor's agent by providing cheaper tools like search_code, outline_file, read_snippet, project_map, and handoff, along with rules that steer the agent to use them and reduce excessive context usage.

An MCP server and VS Code extension that enables AI clients to interactively debug code using breakpoints, execution control, and state inspection. It is language-agnostic and works with any debugger that supports VS Code's launch.json configurations.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Allows AI assistants to access and analyze your Cursor conversation history, enabling personalized coding assistance based on your actual development patterns.

Provides persistent memory and a codebase knowledge graph for AI coding assistants, enabling shared context across multiple tools like Claude, Cursor, and ChatGPT, with significant token reduction.

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.

MCP bridge from OpenCode to Cursor agent CLI, enabling code review, debugging, and planning via Cursor cloud.

Exposes the VS Code/Cursor Problems panel to AI assistants via MCP, enabling live diagnostics querying with filters, context, summaries, and code actions.

Facilitates integration with the Cursor code editor by enabling real-time code indexing, analysis, and bi-directional communication with Claude, supporting concurrent sessions and automatic reconnection.

A MCP server to allow the LLM in Cursor to access Rust Analyzer, Crate Docs and Cargo Commands.

Exposes Cursor's semantic code search through MCP, enabling tools like codebase_search to query indexed repos.

MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

Enables codebase indexing and searching with symbolic and full-text search, supporting multiple programming languages, designed to work on any architecture including ARM64.

MCP server that inspects local codebases and generates source-grounded context packs for coding agents, with tools for repository search, symbols, dependencies, Git analysis, and context generation.

A local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.

Provides codebase indexing and retrieval tools that give AI agents token-efficient, query-relevant context packages (symbols, imports, and dependencies) instead of scanning entire repositories.

An MCP server that acts as a context-aware code retrieval broker for AI coding agents, enforcing backpressure and token budgeting to prevent context window overflow.

Enables LLMs to efficiently read, write, and refactor code using precise AST-based operations, reducing token usage and context window waste.

Enables coding agents to retrieve token-budgeted, source-hashed code context from explicitly registered local repositories via read-only MCP tools, reducing broad repository crawling while providing structure, symbols, and impact slices.

Local code context engine for Codex App/CLI that indexes code with SQLite/sqlite-vec for hybrid search and context packing to provide relevant files, line numbers, snippets, and paths.