
MCP Assist — Coordination Memory
io.github.aliomraniH由 GitHub 帳號 aliomraniH 發布v0.4.1更新於 Oct 24, 2026
Coordination memory with verification: reconcile-against-GitHub, verdict freshness, provenance.
發布方自己的服務:Memory.fit
概覽
面向多代理協作的遠端協調記憶伺服器:透過 Streamable HTTP 提供依命名空間隔離的記憶、交接、工作階段、成品,以及經 GitHub 核驗的結論。
- 可以做什麼
- 儲存、讀取、列出、搜尋、檢視歷史與刪除命名空間內的記憶項目,可選語意檢索
- 記錄與載入代理之間的交接,並建立帶附加式事件日誌的工作階段
- 依 sha256 存取內容定址的成品,支援分段讀取,單件上限 50 MB
- 執行協調檢查:健康狀態、漂移掃描、對照 GitHub 核對結論、把已結束的工作階段整理成記憶
- 開啟意圖、定義技能、關閉閘門結果,並執行伺服器端固定順序的流程(引導、命名空間初始化、召回)
- 記錄觀察回饋並讀取彙總統計
- 適用情境
- 當多個代理或多個用戶端入口(網頁、桌面、命令列、編輯器)需要一個共享且持久的專案記憶、交接與成品存放處,或希望關於 PR 與分支的說法先對照 GitHub 核實再採信時適用。它是不含領域術語的通用儲存,適合任何能依命名空間劃分的專案。
- 執行需求
- 需要連線遠端 MCP 端點(Streamable HTTP),不需在本機安裝套件。必須在 Authorization 標頭攜帶 bearer 權杖(網頁連接器改以查詢參數傳遞),權杖由伺服器上受密碼保護的管理面板簽發與輪換。GitHub 存取、向量嵌入與整理模型等選用整合由服務營運方設定,而非用戶端。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 MCP Assist — Coordination Memory,將其新增到工作區。
- 連接 Authorization token 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.aliomraniH%2Fmcp-assist-memory/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"assist-coordination-memory": {
"type": "http",
"url": "https://mcp-assist-memory.replit.app/mcp",
"headers": {
"Authorization": "Bearer <YOUR_TOKEN>"
}
}
}
}README
mcp-assist-memory
A generic, project-agnostic memory / coordination / artifact server for multi-agent and multi-surface work. One FastAPI process serves a 30-tool MCP over Streamable HTTP, backed by Postgres (+ pgvector), deployed standalone on a Replit Reserved VM.
This is Tier 1 of the reusability contract: every project reuses it as-is. It carries zero domain terms — project identity lives in namespace values, never in tool names, tables, columns, or code.
Capabilities at a glance
- 30-tool MCP over Streamable HTTP (memory, handoff, session, artifact, coordination, feedback, admin).
- Trust-boundary spine (Plan v2) — actor-scoped exactly-once writes with
visible dedup, read-back-verified acks (
verified_persisted), standardized error payloads with remedies, write-time screening + quarantine, provenance tiers (origin, model attribution,derived_fromlineage), trust decay (needs_reverification), PHI-safetool_eventstelemetry, per-namespace variant profiles, and anobservation_logfeedback channel. - Namespace-scoped multi-tenancy — every per-project query filters on
namespace. - Resilient to transient DB drops — the server transparently retries genuine
connection losses (Neon scale-down / PgBouncer recycle, SQLSTATE
57P01/08xxx) on a fresh pooled connection, and validates connections at checkout, so callers no longer have to retry. Retries are idempotency-gated, so they never double-write. - Prompt-injection resistance layer — values are sanitized on write (forged
markers are escaped one-way to
[[UNTRUSTED_DATA]], never reconstructed on read), instruction-shaped writes are screened and quarantined (visible in the write ack;include_quarantined: trueopts reads back in), and reads come back wrapped in<<<UNTRUSTED_DATA>>>markers;storage.sanitize.unwrap_valuerecovers the raw value when a consumer needs it (e.g. tojson.loads). Honest framing: these are layers, not proofs — deterministic screens and wrappers are bypassable by an adaptive attacker; adversarial evaluation is pending (see Phase 10 backlog inDECISION-PROTOCOL.md). - Content-addressed artifacts (sha256, global dedup), 50 MB cap, ranged reads.
- Per-surface rotatable tokens (web vs. desktop-cli) managed from a password-gated
/admindashboard.
The 30 tools
Sequences are the paths an agent should take. Correct use of this server has
always been a sequence — learn which database answered, resolve the profile,
check what is stale, then act — and that ordering used to live in tool
descriptions and skills, i.e. it was enforced by a model remembering advice
mid-task, and a skipped step produced no signal whatsoever. The three sequence
tools run their steps server-side in a fixed order and return steps_run, so
the ordering is something the server did rather than something a caller got
right. They are strictly additive: every primitive they are built from still
works exactly as before, for surgical use.
recall and memory_search now share ONE retrieval guard
(storage/retrieval.py): the same absolute floor and relative alpha the Intent
Gate applies. Previously memory_search had no floor at all while intent_open
had both, so the same store answered the same question differently depending on
which tool the caller reached for. They still differ in what they do with the
verdict — memory_search annotates every row and drops nothing, recall
filters by default and reports the rejected counts — but they can no longer
disagree about what counts as a match.
The Intent Gate (claude/intent-gate/INTENT_GATE_CHARTER.md) is a
per-namespace opt-in (variant_profiles.profile.intent_gate: "on"): mutating
tools gain a deterministic Tier-0 pre-flight (two-phase preview/confirm for
supersession + delete, dependency-freshness flags, compact gate ack block),
intent_open adds the Tier-1 memory-similarity critic, and Tier 2 (LLM
reasoning over the direct Anthropic API — never MCP sampling) ships behind
tier2: "on" (default off). Default-profile namespaces are byte-identical to
the pre-gate server.
/healthz (liveness) and the /admin token dashboard are served separately (not
MCP tools).
Tenancy — namespace is the project boundary
namespace == project == tenant. One namespace per project (e.g.
acme-billing), with conventional sub-scopes by key prefix (coord/…,
knowledge/…). Every per-project tool takes a required namespace and every
query filters on it — there are no implicit cross-project reads. The session
and session_event tables carry namespace too, so episodic memory is scoped
like everything else.
Artifacts are the deliberate exception: they are content-addressed (sha256) and dedup globally, so they are not tenant-scoped — the hash is the capability.
Honest limit (and the v2 fix)
The per-surface tokens scope which client surface connects, not which project it may touch: any holder of any active token can pass any namespace, so namespace remains a soft boundary — real isolation for honest clients, not enforced against a misbehaving one.
v2 auth roadmap — per-project tokens/roles. A token scoped to
acme-billingmust not be able to read or writeother-project. Until then, treat the namespace boundary as a convention enforced by client configuration, not by the server. (See REUSABILITY.md → "namespace is the tenant boundary".)
Auth & the /admin dashboard
MCP tokens are stored in Postgres (admin_auth_tokens) and rotatable from
/admin without a redeploy. There is one active token per surface:
The gate accepts any active token, so each surface can be rotated or
revoked independently — rotating web never disturbs desktop-cli or
cursor. The
/admin page shows one card per surface with a ready-to-paste URL/command and
its own rotate button.
MCP_AUTH_TOKEN seeds the web token on initial boot (so an existing
claude.ai connector keeps working); desktop-cli and cursor are
auto-generated. After first boot the dashboard is the source of truth.
/adminis password-gated byADMIN_PASSWORD(signed, HttpOnly session cookie, CSRF-protected). Without it the dashboard refuses logins.- The only routes not behind the bearer gate are
GET /healthz, the streamedGET /artifact/{sha256}, and/admin(which self-authenticates).
Stateless transport. /mcp runs in stateless HTTP mode
(http_app(stateless_http=True)): every request is self-contained, with no
in-memory session affinity. Client sessions therefore survive VM
restarts/redeploys, and the three surfaces share no server-side session state.
Architecture
- One
AsyncConnectionPoolcreated in the FastAPIlifespan(app.py), injected viadeps. Nothing else opens a connection. The pool is built withcheck=AsyncConnectionPool.check_connection, so a connection terminated server-side while idle is validated and discarded on checkout, never handed to a caller. - One
config.py(pydantic-settings) — the only place secrets are read. StorageBackendABC (storage/base.py) implemented byPostgresBackend; the 18 tools map 1:1 onto it.- Transparent reconnect: reads and idempotent writes retry on a connection
drop (
_retry_on_disconnect), so e.g.OperationalError: terminating connection due to administrator command(SQLSTATE 57P01, Neon scale-down / PgBouncer) is retried on a fresh pooled connection instead of surfacing to the caller. Only genuine disconnects (08xxx/57P0x/ an already-closed connection) are retried — other operational errors (lock timeout, too-many-connections) surface unchanged. Writes retry only when a replay is safe:artifact_put(content-addressed) always, andmemory_save/handoff_save/memory_deleteonly when given anevent_id(exactly-once). Thesession_*writes also retry, with an explicit tradeoff: a drop in the narrow commit-ack window meanssession_createmay orphan an empty, unreferenced session row, andsession_append_eventis at-least-once (a replay can append one duplicate event). For an append-only session log that beats failing the call outright; a save with noevent_idstill runs once and surfaces the error. - Write-path
sanitizestrips forged delimiters/control chars; reads wrap values in<<<UNTRUSTED_DATA>>>markers (lethal-trifecta defense). Note: thevalue(and session-eventpayload) fields come back wrapped, so a consumer that needs the raw value — e.g. tojson.loadsa value that was a JSON string — must strip the markers first. Usestorage.sanitize.unwrap_value(orstrip_untrustedfor a single string); the wrapping stays applied on every read. - Bounded lifespan readiness (no unbounded
pool.wait()), 50 MB artifact cap, ranged blob reads, idempotentevent_idwrites, idempotent blob backfill. - Semantic recall (
memory_search): when aVOYAGE_API_KEYis set, everymemory_saveembeds the entry (Voyage,voyage-3.5-lite, 1024-dim) into a nullableembedding vector(1024)column with an HNSW cosine index, andmemory_searchranks live entries by meaning (embedding <=> query), then backfills keyword/substring matches up tolimit. Embedding is best-effort: it runs before a connection is taken and never blocks (or fails) a write, and with no key the column stays NULL and search degrades to pure keyword — the pre-Phase-3 behavior. Every leg filters onnamespacefirst (no cross-project recall). After enabling a key on an existing DB, embed old rows once withpython scripts/backfill_embeddings.py(idempotent, only touches NULL rows). - Recall tuning (
hnsw.ef_search): the HNSW index is approximate, so a larger store can miss relevant hits unless its query-time recall parameter is tuned.memory_searchsetshnsw.ef_searchper-statement (transaction-local, semantic leg only) fromHNSW_EF_SEARCH(default100; pgvector's own default is40). Higher = better recall, slightly slower search; it must be>=the search limit to take effect. Small stores return the same rows regardless, so the default is safe to leave alone — raise it (e.g.200) if a large tenant reports missing results, lower it toward40to shave latency. Very large tenants can also tune the index build parameters (m,ef_construction); seemigrations/0002_embeddings.sql(changing those requires recreating the index). - Coordination reconciler (
coord_reconcile): when GitHub access is available, aclaim(withmeta.repo+meta.pr/meta.branch) is resolved against live GitHub — is PR #N merged? what is branch X's head? — and stamped with an append-only verdict; without access it staysunverifiable(never a wrongcurrent). Access is sourced in priority order: an explicitGITHUB_TOKEN(read-only repo + PRs), else — on Replit — the connected GitHub account via the Replit connector (token fetched fresh per cache-window so it survives OAuth refresh), else disabled. Resolution is best-effort: a network/API failure yieldsunverifiable, never a blocked write.GITHUB_WEBHOOK_SECRETenablesPOST /webhook/githubto reconcile affected claims on push / pull_request. - Memory curator (
coord_curate): whenANTHROPIC_API_KEYis set, a finished session can be consolidated write-side:coord_curate(namespace, session_id)reads the session's execution trace plus similar existing memories, asks the model what is worth persisting, and applies the resultingADD/UPDATE/MERGE/SUPERSEDE/NOOPoperations deterministically. Every op passes a fail-closed PHI gate first, claims without provenance (meta.repo+meta.pr/branch) are downgraded to notes, supersession sets a validity boundary (history is kept, never deleted), and writes are idempotent (deterministicevent_id) so re-running a session never double-writes. It is best-effort: without the key the curator is disabled andcoord_curateis a clean no-op ({curator_enabled: false, operations: []}), and any model/parse failure yields zero operations — never a wrong write.dry_run=Truereturns the proposed operations without writing.CURATOR_MODELandCURATOR_MAX_OUTPUT_TOKENStune it. Curated rows also carry a secondhyde_embedding, somemory_searchcan match a future question (HyDE leg) as well as the stored statement.
Run locally
Tests (real Postgres)
The suite runs against a real Postgres and skips cleanly if DATABASE_URL is
unset. The neutral test project is proj-test (never a real project name).
CI (.github/workflows/test.yml) spins an ephemeral Neon branch per run,
migrates it, runs pytest, and deletes the branch. Set repo secrets
NEON_API_KEY and NEON_PROJECT_ID to enable it.
Smoke test (the connector handshake)
scripts/smoke_mcp.py performs the exact handshake a Claude connector does —
initialize + tools/list over /mcp with a valid token — and asserts HTTP 200
with the full 30-tool surface, plus the guard rails (no/bad token ⇒ 401,
/healthz db ok). It exists so a transport/auth/host regression (like the
fastmcp 3.4.3 421) can never ship silently again.
-
Blocks a bad build: the in-process half runs in CI via
pytest(tests/test_smoke_mcp.py) against the ephemeral Neon branch — a broken handshake, gate, or tool count fails the build before it can deploy. -
Flags an unhealthy live deploy: run it against the deployed URL after a deploy. It exits non-zero on any failed check:
.github/workflows/smoke.ymlruns this against a live URL on manual dispatch (or a 6-hour schedule); set repo secretsSMOKE_BASE_URLandSMOKE_TOKENto enable it (it no-ops cleanly when unset).
Deploy on Replit (Reserved VM)
- In Secrets, set
DATABASE_URL(pooled endpoint),MCP_AUTH_TOKEN, andADMIN_PASSWORD(plus optional Phase-3 keys). - Deploy as a Reserved VM (
deploymentTarget = "vm") — not Autoscale; the durability gate needs the process to persist. - The deploy
runstep runspython scripts/migrate.pythen starts uvicorn. - Open
https://<your-vm>/admin, sign in, and copy/rotate the token. Point each client athttps://<your-vm>/mcp.
Pinned dependencies (deterministic builds)
pyproject.toml declares loose ranges, but the deploy build, post-merge.sh, and
make install all pass -c constraints.txt, so prod installs the exact versions
verified in dev. This is the guardrail against the class of failure that caused the
prod /mcp 421 outage (an unpinned build silently resolving a newer fastmcp).
To intentionally upgrade a dependency (so pins don't rot):
Never hand-edit versions in constraints.txt; always regenerate with make lock
(scripts/lock-deps.sh). The file header documents the same procedure.
Postgres / Neon
Use the pooled connection string for the running service; psycopg is
configured with prepare_threshold=None for PgBouncer transaction pooling. Tests
and scripts/migrate.py use a direct endpoint (the test pool keeps prepared
statements on).
Boundary
This repo is Tier 1 only. Canvas-specific MCP tools, FHIR logic, and SDK
knowledge live in the separate canvas-sdk-tools repo — never here.
Blob migration (filesystem → bytea)
Idempotent (dedup by sha256), streams each file, skips/reports anything over the 50 MB cap, and verifies a random sample by checksum readback.
來源:README.md,提交 db05997
工具
0版本歷史
1- v0.4.1最新Sep 16, 2026
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