"A tool for storing and maintaining up-to-date codebase memory/context" 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.

Provides Large Language Models with real-time access to the latest documentation for Python libraries like Langchain, LlamaIndex, and OpenAI, enabling accurate and up-to-date code suggestions.

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 159 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

Enables a local LLM to ask the user for guidance via a native desktop pop-up dialog, with configurable options and multiple-choice or free-text input.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

A template for building legal MCP servers that enforces source citation to reduce hallucination, enabling students to create their own grounded legal AI assistants.

A read-only MCP server that lets a Claude chat explore your local repository and answer questions about it, returning synthesized answers with file:line references.

MCP server that provides access to Argentine legal documents (legislation, CSJN jurisprudence, international treaties) with verifiable provenance including SHA256 hashes and source URLs, enabling legal professionals to search and verify citations.

Intelligent context manager for AI coding assistants that uses a three-level memory system (core, active, archive) to remember project context across conversations.

Analyzes software projects to extract architecture, build dependency graphs, and predict the impact of code changes.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Provides local, explicitly scoped memory for coding agents via MCP, storing durable project knowledge in a per-repository SQLite database with tools to record, search, and retrieve context.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Searches Reddit for answers to questions and saves Q&A sessions to Notion.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

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

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

An MCP server that provides AI agents with accurate, system-clock-backed date, time, timezone, and interval information to avoid hallucinations.