"A system like ChatGPT with memory to provide past query context in conversations" matching MCP servers:

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.

Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.

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.

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 secure MCP server that exposes local repository context to ChatGPT/Codex with read-only access, path validation, and no generic shell.

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.

Enables AI agents to create, validate, and export UML system models using structured MSON format. Supports generating PlantUML and Mermaid diagrams with direct export to System Designer macOS application.

Enables AI coding assistants to automatically scan, store, and query API endpoints from codebases, providing instant lookup and semantic search to reduce context switching and token consumption.

Context Bridge is a lightweight MCP server that builds a persistent semantic knowledge graph of your codebase, enabling AI assistants to query complex codebases with sub-millisecond latency without re-reading files every session.

Enables AI coding agents to automatically compile the most relevant slice of a repository into context for a given task.

Provides AI agents with secure, read-only file system access to analyze and understand project codebases, enabling multi-repository context aggregation and cross-project code tracing.

Enables agents to rank and retrieve source files most relevant to a coding task, exposing a pack_context tool that supplies ranked context.

Provides an MCP server for AI coding agents to fetch AST-slimmed source files that keep critical logic like try/catch, auth, and Eloquent relations, cutting context tokens by 50%+.

Enables coding agents to query a local, versioned knowledge graph of a software project, retrieving overviews, context packs, evidence, and explanations to make informed changes.

Provides structured instructions to Cursor for generating comprehensive system summaries of Node.js/TypeScript codebases.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

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.

Enables AI-driven semantic code search using Windsurf's reverse-engineered SWE-grep protocol to query local codebases with natural language. It executes local search tools like ripgrep and tree-node-cli to return relevant file paths and line ranges to MCP-compatible clients.

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.