Skip to main content
AllMCPs
BrowseBestCategoriesStackCompareToolsGuidesBlog
Log in Submit MCP

Stay in the loop

Get new MCP servers and top picks in your inbox.

AllMCPs

The open directory for discovering and installing Model Context Protocol servers.

AllMCPs on GitHub (opens in a new tab)
Launched onTiny Startupstinystartups.com
Explore
  • Browse servers
  • Best MCP servers
  • Categories
  • MCP clients
  • Agent prompts
  • Stack Builder
  • Compare servers
  • Random discovery New
  • Submit a server
  • Pricing & Boost Boost
Learn
  • Guides hub
  • What is MCP?
  • Install guide
  • Build an MCP server
  • Deploy an MCP server
  • Security guide
  • Troubleshooting
  • MCP for SEO & AEO
  • Protocol versioning
  • Blog & updates
Tools
  • All developer tools
  • Config generator
  • Config validator
  • Config auditor
  • MCP playground
  • Token calculator
  • OpenAPI β†’ MCP
  • Badge generator
For agents
  • REST API docs
  • Trust & traffic Live
  • Remote MCP server SSE β†— (opens in a new tab)
  • llms.txt β†— (opens in a new tab)
  • Catalog JSON β†— (opens in a new tab)
Company
  • About
  • Advertise Sponsor
  • Contact
  • GitHub β†— (opens in a new tab)
  • Terms
  • Privacy
AllMCPs VerifiedAllMCPs VerifiedFeatured on Nick LaunchesFeatured on Nick LaunchesLaunch Llama NewsletterLaunch Llama NewsletterVerified DR - allmcps.comVerified DR - allmcps.comFeatured on SaaSGrowFeatured on SaaSGrowFeatured on Twelve ToolsFeatured on Twelve ToolsFeatured on Saaspa.geFeatured on Saaspa.geFeatured on Findly.toolsFeatured on Findly.toolsFeatured on Startup FameFeatured on Startup FameFeatured on LaunchKiwiFeatured on LaunchKiwiFeatured on ScrollLaunchFeatured on ScrollLaunchFeatured on DailyPingsFeatured on DailyPingsFazier badgeFazier badgeFeatured on NewTool.siteFeatured on NewTool.siteFeatured on saasfame.comFeatured on saasfame.comDR Checker - Domain RatingDR Checker - Domain RatingListed on Turbo0Listed on Turbo0Launched on LaunchBoard - Product Launch PlatformLaunched on LaunchBoard - Product Launch PlatformList on SimilarlabsList on Similarlabshttps://codetrendy.comhttps://codetrendy.comListed on DevTool.ioFeatured on BuildlistFeatured on BuildlistLaunched on Tiny StartupsFeatured on ShowMeBestAIFeatured on ShowMeBestAIFind us on LaunchZoneFind us on LaunchZoneAllMCPs VerifiedAllMCPs VerifiedFeatured on Nick LaunchesFeatured on Nick LaunchesLaunch Llama NewsletterLaunch Llama NewsletterVerified DR - allmcps.comVerified DR - allmcps.comFeatured on SaaSGrowFeatured on SaaSGrowFeatured on Twelve ToolsFeatured on Twelve ToolsFeatured on Saaspa.geFeatured on Saaspa.geFeatured on Findly.toolsFeatured on Findly.toolsFeatured on Startup FameFeatured on Startup FameFeatured on LaunchKiwiFeatured on LaunchKiwiFeatured on ScrollLaunchFeatured on ScrollLaunchFeatured on DailyPingsFeatured on DailyPingsFazier badgeFazier badgeFeatured on NewTool.siteFeatured on NewTool.siteFeatured on saasfame.comFeatured on saasfame.comDR Checker - Domain RatingDR Checker - Domain RatingListed on Turbo0Listed on Turbo0Launched on LaunchBoard - Product Launch PlatformLaunched on LaunchBoard - Product Launch PlatformList on SimilarlabsList on Similarlabshttps://codetrendy.comhttps://codetrendy.comListed on DevTool.ioFeatured on BuildlistFeatured on BuildlistLaunched on Tiny StartupsFeatured on ShowMeBestAIFeatured on ShowMeBestAIFind us on LaunchZoneFind us on LaunchZone
Β© 2026 Jackalope Digital LLC. All rights reserved.
  1. Home
  2. 🧠 Knowledge & Memory
  3. Cortex Plugin
Cortex Plugin logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 4:01:23 PM

Cortex Plugin

User RatingsBe the first to rate and review this MCP server!
View Repository32 GitHub StarsTotal stargazers on GitHub for the source repository (32 stars).Visit Website
memorylocalobsidianclaude-codeknowledge-management

Local-first persistent memory plugin for Claude Code storing session lessons as markdown in an Obsidian vault.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
We couldn’t automatically confirm this listing starts correctly

The install command below didn't complete successfully in our automated test.

pipx install memem

/bin/bash: line 1: pipx: command not found

This is an experimental automated check and can have false negatives β€” missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 1mo ago.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "tt-wang-cortex-plugin": {
      "command": "pipx",
      "args": [
        "install",
        "memem"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

This plugin provides Claude Code with persistent, self-evolving memory across sessions by mining durable lessons from conversation turns. It stores these lessons as human-readable markdown files in a local Obsidian vault and assembles relevant context briefings automatically at session start. It requires no cloud services or API keys, ensuring local-first operation and no vendor lock-in. Use it to maintain project knowledge, conventions, and fixes without re-explaining in each session.

Use cases

β€’Persist project decisions and bug fixes across Claude Code sessions
β€’Automatically recall relevant past lessons tailored to current session context
β€’Store and organize AI memory as markdown in an Obsidian vault
β€’Enable local-first memory without cloud dependencies or API keys
β€’Integrate path-scoped memory retrieval based on recent session file activity

Key features

β€’Event-triggered background miner extracting durable lessons from conversations
β€’Stores memories as markdown files in a local Obsidian vault
β€’Active Memory Slice assembling query-tailored context briefings
β€’Path-scoped memory retrieval auto-derived from session file paths
β€’Persistent FTS5 transcript search index for efficient memory lookup
β€’Self-healing install and degraded mode when dependencies are missing

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Cortex Plugin.

Extracted Tool Capabilities
Event-triggered background miner extracting durable lessons from conversations
Stores memories as markdown files in a local Obsidian vault
Active Memory Slice assembling query-tailored context briefings
Path-scoped memory retrieval auto-derived from session file paths
Persistent FTS5 transcript search index for efficient memory lookup
Self-healing install and degraded mode when dependencies are missing

Documentation Overview

memem

Persistent, self-evolving memory for Claude Code. Stop re-explaining your project every session.

CI memem MCP server License: MIT Python 3.11+

For LLM/AI tool discovery, see llms.txt.

Code
  β–ˆβ–ˆβ–ˆβ•—   β–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ•—   β–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ•—   β–ˆβ–ˆβ–ˆβ•—
  β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ•‘
  β–ˆβ–ˆβ•”β–ˆβ–ˆβ–ˆβ–ˆβ•”β–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—  β–ˆβ–ˆβ•”β–ˆβ–ˆβ–ˆβ–ˆβ•”β–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—  β–ˆβ–ˆβ•”β–ˆβ–ˆβ–ˆβ–ˆβ•”β–ˆβ–ˆβ•‘
  β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•  β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•  β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘
  β–ˆβ–ˆβ•‘ β•šβ•β• β–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β•šβ•β• β–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β•šβ•β• β–ˆβ–ˆβ•‘
  β•šβ•β•     β•šβ•β•β•šβ•β•β•β•β•β•β•β•šβ•β•     β•šβ•β•β•šβ•β•β•β•β•β•β•β•šβ•β•     β•šβ•β•
  persistent memory for Claude Code

What is memem?

memem is a Claude Code plugin that gives Claude persistent memory across sessions. An event-triggered miner (Stop-hook β†’ detached mine_delta subprocess) extracts durable lessons (decisions, conventions, bug fixes, preferences) from each new conversation turn, stores them as markdown in an Obsidian vault, and automatically surfaces relevant ones as an Active Memory Slice working state. An explicit narrative assembly path still exists, but the default runtime context is slice-first.

It's local-first: no cloud services, no API keys required, no vendor lock-in. Everything lives in ~/obsidian-brain/memem/memories/ as human-readable markdown.

What's new in v2.9.1 (Path-Scope Activation)

v2.9.1 activates the path-scoped retrieval that shipped dormant in v2.9.0: recall now auto-derives paths_context from the current session so the paths: bonus actually fires without any caller action. The new recent_session_paths() in memem/transcripts.py resolves session_id β†’ JSONL via a direct CWD-slug stat first (O(1)), falling back to next(base_dir.rglob(...), None) (short-circuit on first match); it then tail-reads the last 512 KB of the file (~5 ms even on a 64 MB session, vs ~390 ms for a full read), walks assistant turns most-recent-first, and extracts the top-N deduplicated file paths from Read/Edit/Write/NotebookEdit file_path inputs and Bash command first-line path tokens via _extract_paths_from_content_blocks(). The auto-derivation is wired into active_memory_slice (MCP tool), the auto-recall.sh UserPromptSubmit hook, and the cli.py slice path; caller-supplied paths_context still wins; derivation failures are logged at debug/warning and never propagate β€” any exception returns [] silently. No API or schema changes; 12 new tests in tests/test_recent_paths.py cover extraction, recency/dedup/limit, missing/malformed sessions, and end-to-end active_memory_slice integration. See CHANGELOG for full details.

What's new in v2.9.0 (Tool Diet + Transcript FTS5 + Path Scope)

v2.9.0 trims the MCP surface from 14 tools to 6 β€” removing memory_recall, memory_graph, memory_graph_audit, memory_graph_rebuild, memory_list, memory_import, context_assemble, and memory_remind from the MCP layer (CLI and library equivalents remain for all eight) β€” and cuts total tool-description schema size 57% (12,827 β†’ 5,474 chars). transcript_search is backed by a persistent FTS5 index at ~/.memem/transcript_fts.db (one row per Q/A turn-pair, index_session() called incrementally from mine_delta; old single-row-per-session indexes auto-migrate; the grep fallback is bounded by size/count/time caps and never silently truncates). Path-scoped memories arrive via a new paths: frontmatter field and a 1.05Γ— w_path bonus in retrieve() for memories whose path globs match paths_context; memory_save gains an optional paths param; active_memory_slice accepts paths_context; and the miner annotates candidates with paths: when β‰₯2 paths each appear β‰₯3 times. Telemetry isolation is hardened via MEMEM_TELEMETRY_SOURCE. Closed-loop evaluation tooling is wired: a canary --doctor check, --dual-engine replay, and deferred-gate comments in lessons.py / feedback.py. Benchmark 79.3% (119/150), all acceptance gates pass. See CHANGELOG for full details.

What's new in v2.8.0 (Vault Structure)

v2.8.0 retires the L0–L3 layer system and replaces it with a context model that reflects how memory actually works. The starting point was honest data: 462 memories had been auto-classified L0 ("always relevant"), which was not a layer, it was a full briefing that no session could absorb. The new model has three tiers: (1) profiles β€” schema-shaped always-injected documents per user (profile_user.md: Preferences / Conventions / Environment) and per project (profile_<project>.md: Identity / Stack & Structure / Conventions), stored at <vault>/memem/profiles/, populated by the miner's new PROFILE reconcile op and bootstrappable from your existing vault via --migrate-layers; (2) working rules β€” type:procedural memories (failureβ†’fix patterns, corrections) ranked by citation count and injected as a ## Working rules block at session start (≀1200 chars); (3) episode index β€” the existing 25-entry episodic title index, unchanged. Consolidation logic moves from the deleted consolidation.py into the dreamer's cluster_merge category with a bug fix: only the members listed in supporting_ids are bi-temporally invalidated after a successful merge, not all cluster members unconditionally. The dreamer gains reflection_with_citations (synthesizes type:insight memories from episodic clusters) and tense_rewrite (corrects expired future-tense memories) as additive-safe categories that fire automatically every 25 substantive mining deltas via --dream --safe-auto. The 18-query benchmark improved to 80.0% (120/150) after L0 MMR pre-seeding was removed β€” the anchor mechanism was penalizing relevance, not helping it (measured during release validation; up from 79.3%/119/150 in v2.7.0). See CHANGELOG for full details.

What's new in v2.7.0 (Write Path + Instrumentation)

v2.7.0 makes the miner smarter about what it writes: instead of adding every extracted candidate blindly, it compares each one against its nearest vault neighbors in a single batched Haiku call and picks ADD, UPDATE, SUPERSEDE, or NOOP with safety rails (protected-target guard, truncation guard, ≀5 destructive ops per delta, global fallback to ADD-all on any exception). The previously unreachable bi-temporal invalidation path (invalid_at / replaced_by) is now exercised by SUPERSEDE ops. Every retrieval is now linked to a session id, and the miner scans assistant text for cited memory ids and writes {"type":"citation"} rows to .recall_log.jsonl β€” closing the feedback loop so --analyze-recalls shows citation rate per tool and the dreamer demotion guard is live again after sitting inert since v2.5. Additional improvements: key expansion (miner emits up to 8 synonyms/aliases per memory, FTS+BM25 indexed), tool-trace digest (Bash/Edit decisions are now minable), memory_save three-band dedup (merge instead of reject for 0.70–0.92 near-duplicates), --purge-contaminated --exclude, and flock-safe feedback EMA writes. Benchmark unchanged at 79.3%. See CHANGELOG for full details.

What's new in v2.6.0 (One Engine)

v2.6.0 unifies retrieval: a single three-way RRF engine (cosine + BM25 + FTS5) now serves every call path β€” hook, MCP tools, and CLI. The unbenchmarked heuristic engine that served memory_search/memory_recall since v2.4.0 is deleted (βˆ’218 LOC: 5-signal re-ranker, ngram union, file-scan fallback, and a 15% feedback weight reading a file nothing ever wrote). Deprecated and invalidated memories are now excluded from the retrieval index at vault-load time, fixing a leak via the hook path. The scope_id parameter changes from a hard filter to a soft ranking bonus β€” cross-project results that score well now appear. The 18-query benchmark is maintained at β‰₯74% precision (79.3%, measured during release validation). See the A/B comparison report for transparency on result-set divergence vs the prior engine, and CHANGELOG for full details.

What's new in v2.5.0 (Repair & Prune)

v2.5.0 is a maintenance release: 24 audited defects fixed and ~2,256 LOC of dead code removed. No new memory capabilities. Key fixes: self-mining contamination guard (stale-sweep now skips headless mining transcripts), RRF/MMR scoring bugs fixed (18-query benchmark measured during release validation: 74.7% β†’ 78.7%), embedding index staleness fixed (incremental upsert + mtime invalidation + cross-process flock), double access-count stores eliminated (telemetry sidecar is now the single store), episode deduplication (one stable-id episode per session). Removed: compaction.py, reaper.py, attribution pipeline, storage.py, 8 dead settings knobs, and hybrid injection mode (was documented but never implemented). New CLI: python3 -m memem.server --purge-contaminated [--apply]. See CHANGELOG for full details.

What's new in v2.4.0 (passive mode + episode catalog + telemetry)

Read the full README β†’View source on GitHub β†’

Related MCP Servers

View all in Knowledge & Memory View all alternatives
  • Moxie Docs MCP logoMoxie Docs MCP
    β˜… Featured

    MCP & Agent Skills for Automated Documentation, and codebase conventions + context

    🧠 Knowledge & Memory21 views
    Compare vs Moxie Docs MCP β†’
  • Scrivener MCP logoScrivener MCP

    Connect Scrivener 3 writing projects to Claude and other AI assistants. 47 tools for document management, writing analysis, semantic search, character/plot memory, and content enhancement. Progressive skill loading, relationship engine with HMS triplets, and JS fallback for offline semantic search. npm i -g scrivener-mcp

    🧠 Knowledge & Memory16 views
    Compare vs Scrivener MCP β†’
  • Deja Vu logoDeja Vu

    Local memory layer over the session histories coding agents already write (Claude Code, Codex CLI, opencode): lexical search, recall tools, session-start auto-recall, secret redaction at index time, cross-machine sync over SSH.

    🧠 Knowledge & Memory2 views
    Compare vs Deja Vu β†’
  • MCP Obsidian logoMCP Obsidian

    Universal AI bridge for Obsidian vaults using MCP. Provides safe read/write access to notes with 11 comprehensive methods for vault operations including search, batch operations, tag management, and frontmatter handling. Works with Claude, ChatGPT, and any MCP-compatible AI assistant.

    🧠 Knowledge & Memory4 views
    Compare vs MCP Obsidian β†’

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
32
Stargazers on the source repository.
npm downloads
9
Package downloads in the last 30 days.
Last commit
10d ago
Most recent push to the default branch.
Install check
Inconclusive
Install command did not finish in our automated test.
Directory activity
1 upvotes
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Cortex Plugin

No, it operates fully local-first with no cloud dependencies or API keys required.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:
Live Dynamic SVG PreviewCortex Plugin AllMCPs Directory Badge
Markdown (GitHub README)
[![AllMCPs](https://allmcps.com/api/badge/tt-wang-cortex-plugin?style=directory)](https://allmcps.com/mcp/tt-wang-cortex-plugin)
HTML Embed
<a href="https://allmcps.com/mcp/tt-wang-cortex-plugin"><img src="https://allmcps.com/api/badge/tt-wang-cortex-plugin?style=directory" alt="Cortex Plugin on AllMCPs" /></a>

Technical Specs & Signals

Category🧠Knowledge & Memory
PricingFree
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseMIT
ClientsClaude Desktop
Last updatedSep 1, 2026
5/6 checks healthy over the last 32d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars32
GitHub Star CountTotal stargazers on GitHub representing community popularity (32 stars).
Last commit10d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 1, 2026
npm downloads9/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
60Quality signal: Good Β· 60/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools26/30
Adoption & activity8/15
Community engagement1/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

β˜… FeaturedAllMCPs Server logo

AllMCPs Server

The official MCP server for AllMCPs.com - submit and manage tools directly from your AI. The open directory for MCP servers. Connect Claude, Cursor, Windsurf, and AI agents to databases, tools, files, and APIs. Explore 10,000+ servers. AllMCPs is the premier, open directory for discovering, evaluating, and installing Model Context Protocol (MCP) servers to equip AI agents and LLMs with real-world superpowers.

Explore Server β†’

Own this project?

This directory is pre-filled from public sources. Claim via GitHub README, site badge, or DNS TXT to unlock edit access and the Official badge β€” proof is checked automatically, then reviewed by our team.

Free dofollow backlink: add your website and place the AllMCPs badge on it β€” no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in 🧠 Knowledge & Memory β†’Best MCP servers for Memory & Knowledge β†’Alternatives to Cortex Plugin β†’Install in Claude DesktopInstall in CursorInstall in VS Code