Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Coordination memory with verification: reconcile-against-GitHub, verdict freshness, provenance.
These three are never merged into one score: opinions, measurements and popularity are different things.
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Run this in your terminal
claude mcp add --transport http assist-memory https://mcp-assist-memory.replit.app/mcp --header 'Authorization: your-value'Fill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"assist-memory": {
"url": "https://mcp-assist-memory.replit.app/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"assist-memory": {
"type": "http",
"url": "https://mcp-assist-memory.replit.app/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
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Authorization secret required HTTP headerThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
We have not read this server’s tool list yet; we check endpoints in rotation.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account aliomraniH, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
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It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (0.4.1) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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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.
verified_persisted), standardized error payloads with remedies, write-time screening + quarantine, provenance tiers (origin, model attribution, derived_from lineage), trust decay (needs_reverification), PHI-safe tool_events telemetry, per-namespace variant profiles, and an observation_log feedback channel.namespace.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.[[UNTRUSTED_DATA]], never reconstructed on read), instruction-shaped writes are screened and quarantined (visible in the write ack; include_quarantined: true opts reads back in), and reads come back wrapped in << >> markers; storage.sanitize.unwrap_value recovers the raw value when a consumer needs it (e.g. to json.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 in DECISION-PROTOCOL.md)./admin dashboard.| Group | Tools |
|---|---|
| memory | memory_save memory_get memory_list memory_history memory_delete memory_search |
| handoff | handoff_save handoff_load handoff_list |
| session | session_create session_append_event session_get session_list session_events |
| artifact | artifact_put artifact_get artifact_list |
| coordination | coord_health coord_drift_scan coord_reconcile coord_curate |
| gate | intent_open skill_define gate_close_outcome gate_cache_status |
| sequence | session_bootstrap namespace_init recall |
| feedback | observation_log |
| admin | stats |
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).
`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.
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".)
MCP tokens are stored in Postgres (admin_auth_tokens) and rotatable from `/admin` without a redeploy. There is one active token per surface:
| surface | label | how the client sends it |
|---|---|---|
| claude.ai web connector | web | ?token= in the URL (the web connector can't send headers) |
| Claude Desktop and the Claude Code CLI | desktop-cli | Authorization: Bearer |
| Cursor | cursor | Authorization: Bearer (via .cursor/mcp.json) |
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.
/admin is password-gated by `ADMIN_PASSWORD` (signed, HttpOnly session cookie, CSRF-protected). Without it the dashboard refuses logins.GET /healthz, the streamed GET /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.
AsyncConnectionPool created in the FastAPI lifespan (app.py), injected via deps. Nothing else opens a connection. The pool is built with check=AsyncConnectionPool.check_connection, so a connection terminated server-side while idle is validated and discarded on checkout, never handed to a caller.config.py (pydantic-settings) — the only place secrets are read.StorageBackend ABC (storage/base.py) implemented by PostgresBackend; the 18 tools map 1:1 onto it._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, and memory_save/handoff_save/memory_delete only when given an event_id (exactly-once). The session_* writes also retry, with an explicit tradeoff: a drop in the narrow commit-ack window means session_create may orphan an empty, unreferenced session row, and session_append_event is 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 no event_id still runs once and surfaces the error.sanitize strips forged delimiters/control chars; reads wrap values in << >> markers (lethal-trifecta defense). Note: the value (and session-event payload) fields come back wrapped, so a consumer that needs the raw value — e.g. to json.loads a value that was a JSON string — must strip the markers first. Use storage.sanitize.unwrap_value (or strip_untrusted for a single string); the wrapping stays applied on every read.pool.wait()), 50 MB artifact cap, ranged blob reads, idempotent event_id writes, idempotent blob backfill.VOYAGE_API_KEY is set, every memory_save embeds the entry (Voyage, voyage-3.5-lite, 1024-dim) into a nullable embedding vector(1024) column with an HNSW cosine index, and memory_search ranks live entries by meaning (embedding <=> query), then backfills keyword/substring matches up to limit. 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 on namespace first (no cross-project recall). After enabling a key on an existing DB, embed old rows once with python scripts/backfill_embeddings.py (idempotent, only touches NULL rows).memory_search sets hnsw.ef_search per-statement (transaction-local, semantic leg only) from HNSW_EF_SEARCH (default 100; pgvector's own default is 40). 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 toward 40 to shave latency. Very large tenants can also tune the index build parameters (m, ef_construction); see migrations/0002_embeddings.sql (changing those requires recreating the index).claim (with meta.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 stays unverifiable (never a wrong current). Access is sourced in priority order: an explicit GITHUB_TOKEN (read-only repo + PRs), eOnly the beginning is shown; read the rest in the repo