MCP server for 0Latency — persistent memory layer for AI agents. Give Claude, Cursor, or any MCP client long-term memory.
Zengram is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
Open InstallationWhat it does
Persistent memory for AI agents — pgvector + BM25 keyword search with RRF fusion, credential scrubbing, auto-consolidation.
Quickstart
# 1 — run it from where its publisher ships it
npx -y @zensystemai/zengram-mcp
# 2 — ask your agent something
> Persistent memory for AI agents — pgvector + BM25 keyword search with RRF fusion, credential scrubbing, auto-consolidation.
Zengram is free: there is no plan to choose, no cap to set and nothing that can bill you.
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. This one runs on your machine: your client starts Zengram as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. It is scanned, signed and pinned to the version you choose — read the surface before you approve it.
This is a public server: you run it yourself and this marketplace is not in the path. Claude Code registers it in one command.
claude mcp add zengram-mcp -- npx -y @zensystemai/zengram-mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
One config entry your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.
12 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Multi-path search across all shared memories. Runs vector (semantic) and full-text keyword retrieval in parallel, merged with Reciprocal Rank Fusion into a blended ranking. Returns compact format by default to save tokens. Use format=
Takes no parameters.
Get a session briefing: what happened since a given time across all agents. Excludes entries from the requesting agent by default. Returns compact format (truncated content) to save tokens — use format=
Takes no parameters.
Structured query of shared memories via the database. Query facts by key, statuses by subject, or events by time range. Use brain_search for semantic queries instead.
Takes no parameters.
Get memory health stats: total memories, active vs superseded, consolidated, decayed, breakdown by type. Use this to understand the state of the shared brain.
Takes no parameters.
Trigger a memory consolidation run. An LLM analyzes unconsolidated memories to find duplicates to merge, contradictions to flag, connections between memories, and cross-memory insights. Runs automatically on a schedule, but can be triggered manually. Default action
Takes no parameters.
Query the entity graph. Entities are automatically extracted from memories — clients, people, technologies, workflows, domains, agents. Use this to find all entities, get details about one, or list all memories linked to an entity.
Takes no parameters.
Soft-delete a memory by ID (marks it inactive). The memory remains in storage but is excluded from search results. Agent-scoped keys can only delete their own memories. Use this for compliance or to remove incorrect/sensitive memories.
Takes no parameters.
Update an existing memory\
Takes no parameters.
Export shared memories as JSON for backup or migration. Returns memory payloads (no vectors). WARNING: Can return very large responses — use limit, client_id, type, or since filters to avoid exceeding MCP message size limits. Default limit is 500.
Takes no parameters.
Operator-only: import memories from JSON (e.g. from a brain_export backup). Mutates the memory store, re-embeds with current provider, and deduplicates by content hash. Requires operator_approved=true. Max 500 records per call.
Takes no parameters.
Reflect on a topic by synthesizing patterns across stored memories. Searches relevant memories using multi-path retrieval, then uses LLM to analyze and produce insights about patterns, timeline evolution, contradictions, and knowledge gaps. Use this for
Takes no parameters.
Agentic, iterate-until-sufficient retrieval for HARD MULTI-HOP questions only (e.g.
Takes no parameters.
- Every tool, no call limit
- No card, no account needed
- Source published under a licence you can read
- Runs on your machine — nothing of it reaches our gateway
- Nothing to cap, because nothing bills
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable. Zengram costs nothing to install and nothing to call, at any volume.
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | minimal | capability blast radius (minimal) — client exposure if the model is manipulated | −0 |
| verification-discount | repo | publisher verification (public source) — no provenance, but the source is public and inspectable | −1 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tools were statically extracted from the published source (13 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. minimal is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| brain_store | no tags | |
| brain_search | no tags | |
| brain_briefing | no tags | |
| brain_query | no tags | |
| brain_stats | no tags | |
| brain_consolidate | no tags | |
| brain_entities | no tags | |
| brain_delete | no tags | |
| brain_update | no tags | |
| brain_export | no tags | |
| brain_import | no tags | |
| brain_reflect | no tags | |
| brain_research | no tags |
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
Pinned to 4.5.0 — the install command below asks for that release. A pin is part of an install, so it is kept for this visit and written down when you install.
No release note was published with this version.
Only accounts with at least 50 real tool calls against this server in the last 90 days can post. Ratings are weighted by how much the reviewer actually uses it, and publishers can reply once per review.
Writing one takes an account with at least 50 real tool calls against Zengram in the last 90 days. That is the whole gate — there is no other way to post, which is why the counts beside each review are worth reading.
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes an account with 50 real tool calls against it.