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Nothing to run from here
Cogmemai 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.
81/100
trust score
100
downloads a day
local
runs on your machine
3k
downloads in 30d
What it does
CogmemAi: Autonomous Cognitive Memory for Any Ai System. 95.10% on LongMemEval (top published score on the field's hardest long-term memory benchmark) and 91% on LoCoMo (above human performance). Autonomous memory capture: your Ai's work is saved even whe
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --env 'COGMEMAI_API_KEY=${COGMEMAI_API_KEY}' --transport stdio cogmemai-mcp '--' npx -y cogmemai-mcp
# 2 — ask your agent for something these tools do
# save_memory, save_rule, list_rules and 38 more
It needs COGMEMAI_API_KEY: this reads it from your environment, so export it first.
Cogmemai costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
HIAll 2 servers
hifriendbot2 servers
2 categories
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. This one runs on your machine: your client starts Cogmemai as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. Its scan result is on the Security tab — read the surface before you approve it.
Claude Codedeclared by this listing
This is a public server: you run it yourself and this marketplace is not in the path. You need Node.js — the current LTS (24) is the safe choice; npx comes with it. Claude Code registers it in one command; --scope user makes it available in every project. Claude Code reads COGMEMAI_API_KEY (Your CogmemAi API key from hifriendbot.com/developer/) from your environment each time it starts the server, so the value stays out of its config: export it in your shell profile (macOS, Linux), or run setx COGMEMAI_API_KEY … and open a new terminal (Windows). The '--' is in quotes so that PowerShell passes it on.
claude mcp add --scope user --env 'COGMEMAI_API_KEY=${COGMEMAI_API_KEY}' --transport stdio cogmemai-mcp '--' npx -y cogmemai-mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it runs from its publisher’s own package: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it asks of you
It reaches a system of yours, so it needs your own credential rather than the publisher’s: COGMEMAI_API_KEY — Your CogmemAi API key from hifriendbot.com/developer/. You set it in your own client’s config, on your machine — this marketplace never holds it.
What it writes
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.
What you approve
41 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.
Store a developer memory (fact, preference, decision, architecture detail). Memories persist across all Claude Code sessions and are available in future conversations.
No parameter schema on file.
Save a mandatory rule that will ALWAYS be followed in every session. Rules bypass scoring and decay — they are injected into every conversation, every time. Use for absolute requirements like
No parameter schema on file.
List all mandatory rules for the current project and/or globally. Rules are always-on memories that surface in every session.
No parameter schema on file.
Delete a mandatory rule by its memory ID. Use list_rules to find the ID first.
No parameter schema on file.
No parameter schema on file.
Search stored memories using semantic search. Returns memories ranked by relevance, importance, and recency. Use this to find relevant context from past sessions.
No parameter schema on file.
Extract memories from a conversation exchange using AI. Send the developer message and assistant response, and the server identifies facts worth remembering (architecture decisions, preferences, bug fixes, etc.).
No parameter schema on file.
Load top memories for the current project plus relevant global memories. Use at the start of a session to get full context from previous sessions. Optionally pass context to get memories most relevant to your current task.
No parameter schema on file.
List stored memories with optional filters by type, category, scope, or project.
No parameter schema on file.
Move a memory to the trash by its ID. Trashed memories are hidden from recall and restorable with restore_memory for 30 days, then purged permanently.
No parameter schema on file.
Restore a trashed (deleted) memory by its ID. Works within 30 days of deletion, before the trash is purged. Use list_trash to find restorable memories.
No parameter schema on file.
List trashed (deleted) memories, newest first, with days remaining before each is purged permanently. Restore any of them with restore_memory.
No parameter schema on file.
Update an existing memory
No parameter schema on file.
Delete multiple memories at once by their IDs. Maximum 100 IDs per call. This is permanent.
No parameter schema on file.
Update multiple memories at once. Each item needs a memory_id and fields to update. Maximum 50 items per call.
No parameter schema on file.
Get current usage statistics — memory count, extractions this month, tier info, projects.
No parameter schema on file.
Export all memories as JSON. Use this to back up memories or transfer them to another project.
No parameter schema on file.
Bulk import memories from a JSON array. Each memory needs at minimum a content field. Deduplication is applied automatically.
No parameter schema on file.
Extract memories from a document by splitting it into chunks and processing each one. Great for onboarding — feed in READMEs, architecture docs, or API specs to quickly build project context.
No parameter schema on file.
Save a summary of the current coding session. Captures what was accomplished, decisions made, and next steps. Stored as a session_summary memory for future reference.
No parameter schema on file.
List all tags in use across your memories, with counts. Use this to see what threads/groups exist and find related memories by tag.
No parameter schema on file.
Connect two related memories with a named relationship. Use this to build a knowledge graph — e.g., linking a bug fix to the architecture decision that caused it, or connecting a preference to the pattern it led to.
No parameter schema on file.
View all memories linked to a specific memory. Returns the relationship type and full memory details for each connection. Use this to explore the knowledge graph around a memory.
No parameter schema on file.
View the edit history of a memory. Shows all previous versions with timestamps and what changed. Useful for understanding how a decision or fact evolved over time.
No parameter schema on file.
Get a memory health dashboard with insights: most recalled memories, never-recalled memories, stale memories, growth trends, and breakdowns by type and category. Use this to identify cleanup opportunities and understand memory usage patterns.
No parameter schema on file.
Promote a project-scoped memory to global scope so it applies across all projects. Use this when you discover a preference or pattern that should be universal — e.g.,
No parameter schema on file.
No parameter schema on file.
Create a task that persists across sessions. Tasks are tracked with status (pending, in_progress, done, blocked) and priority (high, medium, low). Use this to maintain continuity on multi-session work.
No parameter schema on file.
Get tasks for the current project. Returns tasks filtered by status — defaults to showing pending and in_progress tasks. Use at session start to pick up where you left off.
No parameter schema on file.
Update a task\
No parameter schema on file.
Save a correction pattern — what went wrong and what the right approach is. These are surfaced automatically when similar situations arise in future sessions, helping avoid repeated mistakes.
No parameter schema on file.
Set a reminder that surfaces automatically at the start of your next session. Use for follow-ups, things to check, or deferred work. Reminders auto-archive after being shown.
No parameter schema on file.
Find memories that may be outdated based on age and access patterns. Returns memories that haven\
No parameter schema on file.
Show what files changed since your last session. Compares the current git state to a snapshot saved when your previous session ended. Helps you understand what happened between sessions.
No parameter schema on file.
Signal whether a recalled memory was useful or irrelevant. Helps improve future recall quality over time. Use after recalling memories to indicate which were helpful vs noise.
No parameter schema on file.
No parameter schema on file.
Analyze memory clusters and extract underlying factual principles or patterns. Principles are observations about your project —
No parameter schema on file.
No parameter schema on file.
No parameter schema on file.
No parameter schema on file.
No parameter schema on file.
Free
$0 forever
- Every tool, no call limit
- No card, and mcprush charges nothing for it
- Source published under MIT
- Runs on your machine — nothing of it reaches our gateway
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Cogmemai or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
Alert at 80% · then the tool returns a normal MCP error
Used this month: —
BTrust score 81 / 100
Release 3.32.3 · scanned 14 Oct 2026
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.
Threat score88
Client score81
Findings11 threat · 0 capability
Capabilityhigh
Coveragesource
Verificationrepo
Surface digest0f7c71105914527413e88878a52165abce06a54e84349146367eb8ae5f7c61d2
Score vectorthreat 88 → client 81
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | high | capability blast radius (high) — client exposure if the model is manipulated | −6 |
| 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 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
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.
Tool surfaceread
Implementation sourceread
Package metadataread
Live transportnot available
Tools were statically extracted from the published source (41 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. high is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| save_memory | no tags | |
| save_rule | no tags | |
| list_rules | no tags | |
| get_intent | no tags | |
| set_intent | no tags | |
| guard_check | no tags | |
| review_work | no tags | |
| delete_rule | no tags | |
| preflight | no tags | |
| recall_memories | no tags | |
| extract_memories | no tags | |
| get_project_context | no tags | |
| list_memories | no tags | |
| delete_memory | no tags | |
| restore_memory | no tags | |
| list_trash | no tags | |
| update_memory | no tags | |
| bulk_delete | no tags | |
| bulk_update | no tags | |
| get_usage | no tags | |
| export_memories | no tags | |
| import_memories | no tags | |
| ingest_document | no tags | |
| save_session_summary | no tags | |
| list_tags | no tags | |
| link_memories | no tags | |
| get_memory_links | no tags | |
| get_memory_versions | no tags | |
| get_analytics | no tags | |
| promote_memory | no tags | |
| consolidate_memories | no tags | |
| save_task | no tags | |
| get_tasks | no tags | |
| update_task | no tags | |
| save_correction | no tags | |
| set_reminder | no tags | |
| get_stale_memories | no tags | |
| get_file_changes | no tags | |
| feedback_memory | no tags | |
| generate_skills | no tags | |
| extract_principles | 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
Integrityfirst-seen
Surface digest0f7c711059145274
Scanned2026-10-14
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
Always latest — the install command names no version, so it installs the newest release when it runs; the current release on file is 3.32.3. Pin a release below and the command asks for exactly that one.
3.32.3
13 Oct 2026
latestNo release note was published with this version.
3.32.2
10 Oct 2026
No release note was published with this version.
3.31.2
1 Oct 2026
No release note was published with this version.
3.29.0
28 Sep 2026
No release note was published with this version.
3.28.1
27 Sep 2026
No release note was published with this version.
3.27.1
24 Sep 2026
No release note was published with this version.
3.25.2
11 Sep 2026
No release note was published with this version.
3.23.0
undated
- The version this listing was on when mcprush began following its releases. The registry was not asked when it shipped, so this row carries no date.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Cogmemai can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
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 a signed-in account that does not publish it, and nothing else.