"Understanding and Writing Unit Tests" matching MCP servers:

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

An MCP service for AI-assisted reasoning and editing on long-form fiction projects. It builds a structured index from scene files for targeted context retrieval.

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables authors to manage characters, chapters, world settings, and plot lines for novel writing, with creative inspiration tools.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Enables local MCP clients to list, read, write, and search notes in an Obsidian vault via an HTTP server running inside Obsidian.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

An MCP-native research assistant — search backend, intent-routing, and writing pipeline that carries a question through search, verification, and writing, delivering whatever research you need: quick answers, verified sources, or a finished document.

MCP server that connects AI coding tools to VibeCompass projects for reading context and writing decisions, conflicts, and session notes.

AI reads your codebase like a book - one page at a time. Pharaoh gives it the index and a map of how every chapter connects.

Provides long-term memory for agents with meaning-based recall, evidence-gated writing, and separate stores per agent mode.

Enables full Obsidian vault operations including reading, writing, searching, deleting notes, managing tags and links, with support for both local and remote access via stdio or HTTP transports.

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

Provides brain-inspired long-term memory for MCP clients, enabling persistent user understanding across sessions with Chinese-optimized hybrid retrieval and evolving user profiles.

Enables AI assistants to maintain persistent understanding of code projects across chat sessions via a SQLite brain that caches structural maps, summaries, and decisions. Provides tools for querying project structure, searching code, and recording insights to reduce token usage and avoid re-analysis.

Feynman's twelve-problems method as an MCP server — a persistent set of long-running problems plus an evoke loop that tests each new trick against all of them. Local, TypeScript, no LLM inside, no API key.

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.