Conventions MCP server

conventions-mcp

Personal memory for durable coding conventions and standing instructions — one store, any MCP-compatible AI client, available in every project. It holds rules like "always use 2-space indent in this language," "never force-push to main," lasting corrections, and long-lived workflow preferences that should carry across future sessions rather than get re-explained every time. It is deliberately not a history of individual jobs or a place for task-specific directions, temporary decisions, current status, or one-off commands.

Why this one

There's no shortage of memory MCP servers — several well-established ones (mem0/OpenMemory, Zep/Graphiti, the official reference memory server, plus a long tail of smaller projects) already do "remember things across sessions." What's different here:

• Narrow taxonomy, not a general note-taking store. Every capture must be a durable rule for future work and gets classified into one of five purpose-built types — convention, instruction, correction, preference, other — plus a project field and topic tags. Task-specific procedures and work history are excluded so retrieval stays precise instead of noisy.
• Deterministic retrieval, not best-effort. Most memory MCPs rely entirely on the calling model noticing a tool description is relevant and deciding to call it — which fails silently and inconsistently. Codex and Claude Code hooks force the agent to call list_rules: SessionStart supplies the instruction, while PreToolUse denies every other tool until the call has happened.
• Transparent by default, not silent. Every capture and update echoes the verbatim stored content and whether it's global or project-scoped back immediately, so a misheard or misclassified rule is visible and correctable on the spot — not something you discover three sessions later via search.
• Fully local at runtime. SQLite + local embeddings, no hosted service, no per-token costs, no API key. The embedding model is downloaded once on first use (or explicitly with conventions-mcp warmup) and then runs locally. Classification (type/topics/projectScoped) is done by the calling agent at capture time, guided by the tool description — it already has the full conversation the thought came from, richer context than an isolated content string would give a separate extractor model.
• Project-scoped without fuzzy matching. A rule can be global (the default) or tied to one specific codebase. Stdio clients derive the project from their working directory; HTTP clients provide an MCP root or an X-Conventions-Project header. The project identifier is never guessed by an LLM from free text.

If what you want is a general-purpose "remember everything" store, or you're not on Claude Code and don't need the hook-driven determinism, one of the more general options above may fit better. This one is for someone who specifically wants a tight, coding-convention-focused memory that stays accurate and doesn't require trusting the model to remember to check it.

What it's tuned to store

Every capture is classified into one of five types by the calling agent, guided by capture_thought's tool description (src/server.js):

Shortened. The full README is on GitHub.