Calm MCP

CALM — Coding Agent Liveness Map

A live, graph-verified map of your codebase — so an AI coding agent can edit with its eyes open instead of grepping in the dark.

Real call graphs instead of vector-similarity guesses. Compiler-verified edges wherever a compiler is available. Hard safety gates on the write path itself, not just warnings an agent is free to scroll past. Measured claims in this README are tied either to a current CALM snapshot or to benchmark artifacts; repo-specific values change as the codebase changes.

New here? Quick start gets you running in under a minute — no clone, no Rust toolchain, works with Claude Code, VS Code, Cursor, Windsurf/Devin Desktop, Codex, Antigravity, and JetBrains. Comparing tools in this category? Jump straight to Proof, not promises. Want the internals? docs/architecture.md covers multi-tier indexing, the SCIP/LSP overlay system, the concurrency model, and the sanitization layer in full.

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The problem

An AI agent that edits code without knowing who calls the function it's about to change will, sooner or later:

• Delete "dead code" that a dozen other files still call.
• Change a signature and miss half its call sites.
• Refactor a symbol it assumed was minor — and discover, after breaking the build, that it was the hub the whole module leaned on.

None of that is a reasoning failure. It's a *visibility* failure: the agent never had a map. Give it one, and the guessing stops.

Why "CALM"

Most coding agents operate the way anyone would in an unfamiliar codebase with only grep: no sense of what's wired to what, no way to know if touching this function ripples into fourteen others. That's not confidence — it's fast guessing.

CALM stands for Coding Agent Liveness Map. *Liveness*, because the map is never a stale snapshot — it watches the filesystem, reindexes incrementally as files change, and reports in every response how fresh it currently is (scanning → parsing → building_edges → ready). *Map*, because it's an actual graph — call edges, import edges, hub/coreness metrics — not a flat text index pretending to be one. Hand an agent a live, trustworthy map of the terrain, and it stops flailing. It gets calm.

What you get

• The agent stops guessing who depends on what. callers/callees/edit_context show every known caller before a change ships. Full tree-sitter call graphs cover 13 languages out of the box: Python, TypeScript, JavaScript, Java, Rust, and Go with zero configuration, plus C, C++, C#, Ruby, PHP, Shell, and R via the default tier0-5 grammar bundle. Eleven more (Kotlin, Swift, Scala, Dart, Lua, Elixir, Haskell, OCaml, Zig, PowerShell, Groovy) parse behind opt-in --features lang-X build flags — 24 languages parsed in total (see multi-tier indexing).
• Edits that can't silently break things. Every write is hash-verified against the exact line range and syntax-checked before it ever touches disk. Hub and high-fan-in symbols hard-refuse a write until the agent has reviewed the callers and explicitly confirmed — a policy only a tool with a real dependency graph can enforce, and one the published competitor benchmark found no other server enforcing.
• Every edge tells you how much to trust it. Call edges are confidence-graded (textual → inferred → resolved → formal), and when your compiler can double-check the graph, CALM asks it to: SCIP overlays (rust-analyzer, scip-go — including multi-module go.work workspaces — scip-python, scip-ruby, and more) and live LSP overlays (gopls, clangd) can upgrade best-guess edges to compiler-verified ground truth across 12 supported language integrations when their provider/toolchain is available; unavailable providers sit out without changing the base behavior.
• A codebase that grades itself. fitness_report turns hub concentration, dead code, complexity, and architecture-boundary violations into a queryable, CI-enforceable signal instead of a one-off audit — and remember/recall keep decisions and gotchas available across sessions.
• Plays well with others, and stays on your machine. A cross-process edit lock and single-writer indexing model mean two editor sessions on the same repo don't corrupt each other's writes or double-index — under the shared daemon, sessions can even see each other coming. No code leaves your machine for indexing, search, or editing; the default embedding model is vendored into the binary at build time and needs no runtime network when those weights are valid; if they are unavailable, a runtime fallback download is allowed by default and can be disabled for strict offline operation. MIT-licensed. *(One more opt-in exception: building with --features otel and setting OTEL_EXPORTER_OTLP_ENDPOINT exports span attributes — file paths, symbol names, tool names, timing, never source bodies — to your own collector. Off by default; see docs/architecture.md and use https:// collectors only.)*

Where CALM fits

"Code intelligence for AI agents" is a real category now, built up by open-source pioneers — Aider, Serena, Sourcegraph/Cody, and others — that proved an agent works better with real code structure under it than with grep and good intentions. CALM builds on that foundation with a different center of gravity: most tools in the category inform the read path — better search, better navigation, better context. CALM also guards the write path. The same graph that answers "who calls this?" enforces "you don't change it until you've looked": hub/high-risk edits require fresh pre-edit context plus explicit confirmation grounded in a real caller; the policy can be widened to every edit, and every write is hash- and syntax-verified before it lands.

The trade-off is stated plainly: CALM's full-call-graph tier out of the box is 13 languages, not the 40+ some pure-LSP tools reach — though with 24 languages parsed and 12 carrying a compiler-verified upgrade path when their providers are available, the gap is narrower than it looks. What the trade buys is the part most distinctly CALM's own: confidence-graded edges, hard pre-edit gates, and a codebase that grades its own health — each backed by a number you can reproduce yourself (Proof, not promises).

Is CALM the right fit?

Good fit: agents that edit code directly, not just answer questions about it · single-repo codebases in a Tier-0/Tier-0.5 language · projects running multiple MCP clients (see supported clients below) against the same repo · local-first users who don't want to depend on an embedding API.

Not the fit today: multi-repo/cross-repo enterprise search — tools purpose-built for that scale (Sourcegraph/Cody among them) will serve you better · a language nowhere in CALM's current 24-language tree-sitter set.

Quick start

Supported clients — CALM works with any MCP client that speaks stdio; these are wired up or documented today:

Full walkthrough for every client above, including exact global-config snippets for the ones that need one — docs/mcp-client-setup.md. Running inside a devcontainer/Codespace where stdio forwarding doesn't reach? See docs/http-transport.md (advanced, remote-dev only, opt-in, loopback by default).

Using CALM on your own project — no clone, no Rust toolchain:

{

"mcpServers": { "calm": { "command": "npx", "args": ["-y", "@eilodon/calm-mcp", "serve"] } } }

Drop that into .mcp.json (Claude Code/Cursor) or .vscode/mcp.json (VS Code uses a top-level "servers" key instead of "mcpServers", same shape otherwise) at your project root. Claude Code plugin instead: /plugin marketplace add Eilodon/CALM then /plugin install calm@CALM.

Prefer a native binary over npx? curl -fsSL https://raw.githubusercontent.com/Eilodon/CALM/main/scripts/install.sh | sh, then run calm setup from inside your project — it writes the same MCP config automatically, pointing at the binary you just installed. Add calm setup --npx instead to write the portable npx entry (shareable/committable — teammates and CI don't need the binary). It pins to this binary's own version by default for reproducible cold installs; pass --track latest to always resolve npm's newest release instead.

Developing on CALM itself (this repo):

# 1. Build the binary

cargo build --release -p calm-cli

2. Initialize config for your project

calm init --project-root .

3. Build the index (embeds symbols too, if semantic search is enabled in config.json)

calm index --project-root .

4. Run the MCP server over stdio — incremental reindex kicks in automatically if an index already exists

calm serve --project-root .

This repo ships ready-made config for Claude Code (.mcp.json), Cursor (.cursor/mcp.json), and VS Code (.vscode/mcp.json) — all three point at scripts/mcp-launcher.sh, a shared launcher that finds an already-built binary, downloads a checksum-verified prebuilt release if you're on a matching git tag, or builds from source if nothing is available yet. Clone the repo and it just works — no manual build step required first.

Note: calm serve automatically adds .calm/ to .gitignore on startup so the index database never gets committed.

Example: an agent's actual workflow

agent: repo_overview()

→ current files/symbols and indexing_phase=ready are reported live

agent: "I need to change getUserByEmail" → locate("getUserByEmail") # find the file + symbol metadata → source("getUserByEmail") # read just the function body, not the whole file → edit_context("getUserByEmail") # MANDATORY before any edit → the live caller count and risk assessment determine whether the agent reviews callers before touching the signature → edit_symbol("g