"General context or information search" matching MCP servers:

Share context, detect file conflicts, and send messages across parallel Claude Code sessions

Reduces token consumption for AI coding agents by 50-70% through intelligent code context filtering, Git delta tracking, and local SQLite/Tree-sitter indexing.

A local-first bridge for moving useful context between coding agents, indexing sessions and creating handoff packets for seamless agent switching.

MCP server to provide Jira Tickets information to AI coding agents like Cursor

An MCP server that allows coding agents to search the Swift Package Index and retrieve GitHub READMEs without requiring an API key. It features comprehensive search filters for stars, platforms, and licenses, providing token-efficient responses optimized for LLM comprehension.

A Model Context Protocol server that enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

A token-efficient, codebase-aware AI agent runtime that provides MCP tools for starting runs, getting run states, explaining code, and finding files.

Enables coding agents to incrementally index project text and code, persist decisions and constraints with clear sources, and assemble focused project context across sessions via MCP.

Enables semantic code search across projects using AI embeddings to find code by meaning rather than just text matching. Provides fast intelligent search, symbol analysis, and code similarity detection with multi-language support.

Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.

An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.

Enables AI coding agents like Claude Code or Codex to delegate tasks to a DeepSeek Harness subagent with its own context window, providing tools for task delegation, result waiting, continuation, and supervision with sandboxed execution.

A robust, language-agnostic Model Context Protocol (MCP) server that provides AI coding agents with the ability to edit files surgically via Abstract Syntax Trees (AST) instead of relying on token-heavy, brittle search-and-replace or diff operations.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

Connects AI coding agents to the SkillsMP marketplace, allowing users to search, read, and install over 8,000 community-made skills. It enables agents to gain new capabilities either through on-the-spot instruction or permanent installation without requiring an API key.

Provides coding agents with repository context through tools that generate AGENTS.md files or structured JSON summaries, quoting build/test commands from the repo's manifests for a small fee without an API key.

Runs as an MCP server providing file system operations, shell execution, and system information tools, allowing Claude or any MCP client to edit files and control the machine.

A zero-cost MCP server that forces AI to self-correct code using prompt injection and context isolation.

A Model Context Protocol server that provides powerful regex-based code refactoring and search tools for Coding Agents.

A fast, hardened MCP server that lets any MCP host drive the Cursor Agent CLI for heavy repo-aware tasks like search, analysis, planning, and edits, keeping host context small and token costs low.