
Calm Mcp
io.github.Eilodon由 GitHub 帳號 Eilodon 發布v0.8.0更新於 Oct 24, 2026
MCP server giving coding agents a call-graph-aware, hash-verified view of a codebase, not grep.
概覽
一個本機 MCP 伺服器,為編碼助理提供即時、經雜湊驗證的程式碼呼叫圖,用來追蹤呼叫端並在安全閘門下修改程式碼。
- 可以做什麼
- 定位與概覽:儲存庫概覽、熱點、健康度與測試缺口報告、索引狀態、符號與檔案搜尋、原始碼讀取與符號檢查、批次符號查詢,以及透過呼叫端、被呼叫端與路徑追蹤相依關係,並對重新命名或刪除做引用影響分析。帶驗證的編輯:編輯前必須取得脈絡,經雜湊驗證的行級與符號級修改,格式化,提交前的變更影響檢查,以及計畫與審閱授權流程。編輯交易管理:交易與維護狀態、重試、一致性修復和隨需驗證。工作階段回復與記憶:工作階段脈絡、保存決策並在後續工作階段中回想。進階功能:重新整理編譯器與語言伺服器覆蓋層、對任意文字做注入與憑證掃描、依工作階段縮減工具集,以及打包好的審閱、除錯、上手與 PR 審閱提示詞。
- 適用情境
- 適合助理直接修改單一儲存庫程式碼、且需要在改動函式前了解誰在呼叫它的情境,尤其是多個 MCP 用戶端共用同一儲存庫的專案。不適合跨儲存庫的企業級搜尋,或不在其支援語言範圍內的專案。
- 執行需求
- 以 stdio 在本機執行,通常透過 npx 從 npm 套件啟動;未宣告需要帳號或 API 金鑰。編譯器或語言伺服器工具鏈為選用,僅用於提升呼叫邊的可信度。預設嵌入模型已隨程式打包,除非關閉離線回退,否則可能發生一次性模型下載。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Calm Mcp,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
CALM — Coding Agent Liveness Map
[License: MIT] [CI] [npm] [Languages]
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.
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_contextshow 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 defaulttier0-5grammar bundle. Eleven more (Kotlin, Swift, Scala, Dart, Lua, Elixir, Haskell, OCaml, Zig, PowerShell, Groovy) parse behind opt-in--features lang-Xbuild 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-modulego.workworkspaces —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_reportturns hub concentration, dead code, complexity, and architecture-boundary violations into a queryable, CI-enforceable signal instead of a one-off audit — andremember/recallkeep 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 oteland settingOTEL_EXPORTER_OTLP_ENDPOINTexports span attributes — file paths, symbol names, tool names, timing, never source bodies — to your own collector. Off by default; see docs/architecture.md and usehttps://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:
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):
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 serveautomatically adds.calm/to.gitignoreon startup so the index database never gets committed.
Example: an agent's actual workflow
Proof, not promises
The table below is a CALM snapshot observed on 2026-08-12 from this checkout. Re-run repo_overview() and fitness_report() to refresh it; repo-specific values change as the codebase changes. Benchmark ratios are task-specific and remain in the benchmark artifacts:
Competitor-benchmark methodology and per-language caveats
Benchmarked against four other live MCP servers
benchmarks/b11_extended_competitor_ab/ installs and calls four established open-source code-intelligence MCP servers — CodeGraph, Semble, grepai, and Serena — against an isolated git worktree of this repo, 5 repeats per task, with a correctness oracle for every task. The goal isn't a leaderboard; it's checking CALM's claims against real, running prior art instead of a marketing page.
What the runs showed: CALM matched the best result on caller-recall and blast-radius tasks, and was the only one of the five servers whose pre-edit safety gate actually refused a risky, unconfirmed edit rather than merely being able to describe the risk after the fact. Not every number flatters: on one token-efficiency task CALM's compression ratio was the lowest of the five — correctness stayed at the ceiling there too, and the number is published as measured. That is this project's standing benchmark policy: unflattering results ship alongside good ones (benchmarks/README.md). Full methodology, every task, and the raw per-tool numbers live in the benchmark's own README.
Language coverage, measured not asserted
benchmarks/resolution/ runs a tier-distribution baseline (resolved / inferred / textual / ambiguous split — no oracle, one real OSS repo per language) across the 19 newly-added or Tier-0.5 languages, reported as-is: Kotlin (89.6%) and OCaml (86.3%) land mostly in the ambiguous tier from common short method-name collisions; Dart produces symbols but zero call edges — a documented limitation of that tree-sitter grammar, not a bug; Tier-2 type inference is wired only for the original Tier-0 languages so far. Full per-language table in the benchmark's own README.
How CALM works
Full technical detail lives in docs/architecture.md — including the design philosophy behind why every response carries suggested_next and why the risky steps are hard-gated instead of just recommended. Section-by-section summary:
- Multi-tier indexing — 13 languages with full call graphs by default, 11 more parsed behind opt-in grammar features, 24 in total.
- A call graph you can actually trust — every edge is labeled by confidence (
resolved/inferred/formal/textual); SCIP and LSP overlays can upgrade edges to compiler-grade ground truth across 12 supported integrations when their providers/toolchains are available; unavailable providers sit out. - Search that actually finds things — FTS5 + semantic embeddings fused via Reciprocal Rank Fusion, plus real grep/glob straight off disk for files the indexer never parses.
- Editing with an actual safety net — hash-verified writes, syntax validation before anything touches disk, and a three-part gate (fresh
edit_context,confirm:true, a groundedreason) on hub/high-risk symbols. - Concurrency & reliability — a shared daemon, cross-process edit lock, and single-instance indexing lock mean multiple editor sessions on one repo don't corrupt or duplicate work.
- The codebase grading itself — 11 fitness metrics, coverage-aware dead-code detection, declared architecture boundaries, doc-drift detection.
- An agent that remembers, and knows when it's stuck — durable cross-session notes, git co-change mining, a stuck-loop signal.
- Safe by default — credential-shaped content is redacted in
source/understand, prompt-injection-shaped content is flagged, andscan_textcovers external text; local-first by default with an explicit embedding fallback.
Crate layout
crates/calm-core/— the index engine:tree-sitterparsing, SQLite schema, the multi-tier resolver (conservative → inferred → formal/Stack-Graphs, SCIP, or LSP), graph algorithms (coreness, hub detection), FTS5/semantic search, analysis (hotspots, coverage, codeowners, diff-impact, dead-code), fitness metrics, gitignore management.crates/calm-server/— the MCP server (rmcpover stdio or a unix-socket daemon), exposing 40 tools plus the incremental file watcher.crates/calm-cli/— the CLI:calm init,calm index,calm serve,calm connect,calm setup,calm fitness-check,calm guard,calm doctor.
CLI reference
40 MCP tools for AI agents
CLI presets filter tools by workflow phase: orient, trace, edit, compound, full (default) via calm serve --preset or the preset field in config.json — or compose a custom set from toolset (module) names, e.g. --preset "trace,security" or --preset "full,-edit" (see AGENTS.md for the full toolset list). Every response carries suggested_next to point at the next step — full detail on each tool and the complete workflow lives in AGENTS.md.
| Recover | session_context, remember, recall |
| Advanced | scip_refresh, lsp_refresh — force one or every SCIP/LSP provider to run now, bypassing the automatic refresh policy. scan_text — run the same prompt-injection/credential heuristics source/understand use against any text you supply (a WebFetch/WebSearch result, a subagent's report, pasted content) — local and offline, independent of any hosted LLM safety classifier. set_toolset — narrow or reset which tools this session exposes at runtime, without restarting the server (the safety floor — orient+guardrails+recover+edit — is always kept). All four: full preset only, not in the four workflow-phase presets above — deliberate manual/rare-use escape hatches, not steps in the default flow |
MCP Prompts — workflows packaged as slash-commands
Distinct from the tools above — MCP Prompts (prompts/list, prompts/get) return a single ready-made instruction message for a workflow you repeat often; MCP clients surface them as slash-commands:
One-line CI: the CALM Guard GitHub Action
action.yml wraps calm index + calm guard as a reusable composite action -- one-line adoption for a repo that just wants blast-radius review on every PR, no MCP client involved:
On a pull_request event it auto-detects the PR's base branch (fetching just that ref, since a default shallow checkout won't have it) and reviews the merge-base-relative range; on a plain push it reviews before..after. Both are overridable with base/commits inputs matching calm guard's own --base/--commits flags (see CLI reference above) -- set one explicitly for anything the auto-detection doesn't cover (workflow_dispatch, a merge-queue event, etc.). Requires an npm-published @eilodon/calm-mcp release reachable from the runner; nothing else to install.
Fitness check — the CI gate
Run for real in .github/workflows/ci.yml's fitness-check job on every push/PR — calm index first (a fresh checkout has no .calm/index.db yet), then calm fitness-check --project-root . --config thresholds.toml. That --config flag is not optional: without it, [[boundaries]] and [config_drift] are silently treated as "no rules declared" rather than erroring — only the numeric thresholds have a real default.
calm fitness-check measures 11 metrics against thresholds declared in thresholds.toml:
Unless noted above, the table uses built-in numeric defaults; this repo's checked-in thresholds.toml is the effective CI policy. Every calm fitness-check run also snapshots metrics to the DB so edit_context can show a trend (delta versus the previous day).
Architecture boundaries — [[boundaries]]
Declare "module A must not import module B" directly in thresholds.toml (same file as [thresholds]), matched by path prefix (not glob/regex). Note this is for layering Rust's own crate/module boundaries don't already enforce — declaring "calm-core must not import calm-server" would be a no-op, since Cargo's dependency graph makes that structurally impossible already:
calm fitness-check reports each violation concretely (the real from/to path, the rule, and the reason) outside --json mode; the default max_boundary_violations = 0 means a rule you bothered to declare is one you actually keep.
This repo's own thresholds.toml currently declares two: the one above, plus crates/calm-server/src/watcher.rs → crates/calm-server/src/tools/ ("the background reindex/watch loop must not depend on the MCP tool-handler layer it runs independently of") — both hold at 0 violations.
Deployment
cargo build --release→ static (musl on Linux) binaries via.github/workflows/release.yml, 5-target matrix withSHA256SUMS+ build-provenance attestation for every asset:x86_64-unknown-linux-musl,aarch64-unknown-linux-musl,aarch64-apple-darwin,x86_64-apple-darwin,x86_64-pc-windows-msvc.scripts/mcp-launcher.sh/scripts/install.shdownload and checksum-verify the right platform's build automatically on supported targets when checkout is on (or you're installing) a matching git tag; untagged, offline, or unsupported-platform paths fall back to an existing binary or a source build.Containerfile, multi-stage (rust:alpine→scratch) — a single static binary, no runtime image needed, published toghcr.io/eilodon/calm-mcp(tagged by version +latest) on every git tag push.compose.yamlships a hardened example (read_only,cap_drop: ALL,no-new-privileges,pids_limit: 64,mem_limit: 256m).- The default embedding model's weights are vendored into the binary via
include_bytes!—build.rs::ensure_embedding_weightsfetchescrates/calm-core/assets/potion-code-16m/*.safetensorsfrom Hugging Face Hub and checksum-verifies it once at compile time, so a normalcargo build/release binary needs no network I/O at runtime when those weights are valid. No Git LFS is involved (the repo carries zero LFS content).
What happens if the build-time fetch fails (offline build, etc.)
cargo build still compiles successfully — build.rs writes a small placeholder stub in place of the real weights instead of failing the build. Loading that stub at runtime fails ("failed to parse safetensors"), so Embedder::load automatically falls back to a one-time Hugging Face Hub download of the same model (cached locally afterward; the default config allows this fallback, while semantic_search.allow_network_fallback = false keeps the runtime strictly offline). If that fallback is disabled or also unavailable, indexing_status reports embeddings_status: "failed" and search(kind="semantic"/"hybrid") degrades to FTS-only — no crash, just no semantic search until the model is available and you rebuild or re-run.
Runtime and transport
- Default mode is MCP stdio. The launcher uses the shared Unix daemon when invoked without extra launcher arguments on Unix; custom invocations, CI, and Windows can use one-process
calm serve. - HTTP is opt-in.
calm serve --httpbinds to127.0.0.1:8787by default. Non-loopback exposure requires--allow-remoteand a non-emptyCALM_HTTP_TOKENsent as a Bearer token. - Remote HTTP is read-only. CALM forces the effective preset to
remote-safe— every tool that declaresread_only_hint = true, computed from the tool router itself rather than a hand-maintained list, so it can't silently miss a newly added state-mutating tool; terminate TLS at a reverse proxy. The built-in HTTP transport caps request body size and concurrent requests as defense-in-depth, but has no real rate limiting or per-IP DoS protection, so do not expose it directly to an untrusted network.
Testing
Eleven CI jobs run on every PR (verified against .github/workflows/ci.yml's own job list, not hand-counted): verify (fmt/clippy/test/audit), calm-guard-dogfood (dogfoods action.yml against this repo's own PRs — continue-on-error: true, shadow mode while new), stack-graphs-corpus (formal-resolver parity), txn-crash-injection (WS-1's crash-injection suite — kills the process at every reachable TxState transition, real SIGKILL), embeddings (clippy + test with the embeddings feature), no-stack-graphs-formal (clippy + test with stack-graphs-formal off — the only CI coverage of the resolver::formal stub that feature gate compiles to), all-languages (fixture-repo indexing across all 24 parsed languages, plus lsp-overlay), js-client-interop (cross-checks the tool schema against a real JS MCP SDK client, not just Rust's own), otel-http-features (clippy + test with the otel/http features, plus a guard against opentelemetry core version skew), fitness-check (runs calm fitness-check against this repo's own index — see Fitness check below), status-drift (fails the build if docs/status.generated.md is stale, if any hand-authored doc's tool count drifted from it, or if the benchmark claims registry is structurally inconsistent).
The workspace contains 1,000+ tests; the latest CI verify job is the source of truth for pass/fail. A handful of #[ignore]d live-binary integration tests (e.g. rust-analyzer/scip-go/scip-java) need external tools not installed in every environment.
Further reading
docs/architecture.md— the full technical deep-dive: multi-tier indexing, SCIP/LSP overlays, search internals, the edit safety net, concurrency, self-grading, memory, sanitization, and the design philosophy behind it all.docs/comparison.md— methodology-first positioning write-up against other tools in this category.docs/what-external-users-get.md— exactly what annpx/npm/MCP-Registry install gives you, as distinct from this repo's own dev checkout: install/distribution mechanics, the full tool and toolset breakdown, the edit safety layer, language coverage, and what never ships externally.docs/— resolver internals, migration plans, and other design notes not covered bydocs/architecture.mdabove.docs/adr/— individual architecture decision records (Stack Graphs scope, the formal-resolver approach, the LSP-optional confidence upgrade, the daemon+forwarder concurrency model).docs/mcp-client-setup.md— every MCP client install path in detail, including Windsurf/Devin Desktop and Codex global config.docs/http-transport.md— the opt-in remote/HTTP transport (calm serve --http): loopback-by-default, the fail-closed--allow-remote+ token requirement, why remote exposure forces a read-only preset, and the TLS/reverse-proxy expectation.AGENTS.md— the full tool-by-tool workflow guide this project's own agents follow.KNOWN_LIMITATIONS.md— an honest list of what CALM doesn't do yet (single-language unsandboxed verification, no multi-file change-set, no reference-impact tool, risk classification with no change-kind signal, and more), and why each is deliberately deferred rather than half-built.benchmarks/— the measurement suite behind benchmark claims in this README, and a few more:b2_call_graph_quality/(precision/recall vs. a SCIP oracle),b3_search_quality/(hybrid RRF vs. FTS-only vs. raw grep, NDCG@10),b4_token_efficiency/(token cost vs. a naive baseline, per task),b6_tool_call_efficiency/(round-trips: naive multi-call vs. one MCP call),b7_task_correctness/(real rename refactors across 6 language corpora — fd/Rust, flask/Python, express/JS, zod/TS, gin/Go, spring-petclinic/Java — checked against an independent pass/fail oracle, not an LLM judge),b11_extended_competitor_ab/(real calls against 4 other live MCP servers, not self-reported numbers),b12_tier1_tier2_tool_correctness/(9 tools driven live over JSON-RPC against 6 external OSS repos, ground-truthed against regex/git grep),resolution/(tier-distribution baseline across 19 real OSS repos, one per language). Unflattering results are published alongside good ones on purpose —benchmarks/README.mdstates that policy.
License
來源:README.md,提交 ffafc36
工具
0版本歷史
1- v0.8.0最新Sep 16, 2026
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