What types of memory does Mengram support?

Mengram supports semantic memory (facts), episodic memory (events and decisions), and procedural memory (workflows that evolve from failures).

Is Mengram multilingual?

Yes, Mengram supports native multilingual retrieval and answering across 23 languages using Cohere multilingual embeddings and reranking.

Can Mengram be used without an account?

Yes, you can try Mengram locally without an account using 'mengram try', but to use the full API you need a free API key from mengram.io.

Does Mengram support multi-user environments?

Yes, it provides multi-user isolation to keep data separate between users.

Mengram

memoryknowledge-graphmultilingualclaude-codeai-agents

AI memory layer with semantic, episodic, procedural memory, multilingual retrieval, knowledge graph, and Claude Code hooks.

Quick Install

Automated & IDE Setup

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

Add to Cursor Add to VS Code

We couldn’t automatically confirm this listing starts correctly

We ran the install command below but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

uvx mengram-ai

No response to initialize.

This is an experimental automated check and can have false negatives — 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 ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "alibaizhanov-mengram": {
      "command": "uvx",
      "args": [
        "mengram-ai"
      ]
    }
  }
}

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

Overview

Mengram provides a human-like memory system for AI agents supporting semantic facts, episodic events, and evolving procedural workflows. It includes native multilingual retrieval across 23 languages, a knowledge graph, and multi-user isolation. The server integrates with Claude Code via hooks for auto-saving, auto-recall, and cognitive profile loading, enabling persistent memory that survives session clears and compaction.

Use cases

Add and retrieve semantic facts and user preferences

Recall episodic events and decisions from past interactions

Manage and evolve procedural workflows based on failures

Integrate persistent memory with Claude Code agents

Query knowledge graph data with citations in multiple languages

Key features

Semantic, episodic, and procedural memory types

Procedures evolve from failure feedback

Native multilingual retrieval (23 languages)

Knowledge graph and smart triggers

Claude Code hooks for auto-save, auto-recall, and session persistence

Multi-user data isolation

Capabilities & Tool Schemas

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

Extracted Tool Capabilities

Semantic, episodic, and procedural memory types

Procedures evolve from failure feedback

Native multilingual retrieval (23 languages)

Knowledge graph and smart triggers

Claude Code hooks for auto-save, auto-recall, and session persistence

Multi-user data isolation

Documentation Overview

Give your AI agents memory that actually learns

Website · Get API Key · Docs · Console · Examples

Terminal

pip install mengram-ai   # or: npm install mengram-ai

mengram try              # see what memory would know about you — local only,
                         # no account, nothing leaves your machine

server.ts

from mengram import Mengram
m = Mengram(api_key="om-...")           # Free key → mengram.io

m.add([{"role": "user", "content": "I use Python and deploy to Railway"}])
m.search("tech stack")                  # → facts
m.ask("what's my tech stack?")          # → synthesized answer + citations
m.episodes(query="deployment")          # → events
m.procedures(query="deploy")            # → workflows that evolve from failures

Native multilingual: ask in Russian, Chinese, Spanish, Japanese — Mengram retrieves and answers across 23 languages (Cohere multilingual embeddings + rerank).

Install in one prompt (any AI tool)

Paste this into Claude Desktop, Cursor, Codex, Claude Code, or Windsurf — the agent reads our setup guide, installs the SDK, configures the MCP server, and verifies the round-trip end-to-end. No terminal context-switching.

Code

Install Mengram for me. Fetch the canonical install guide at
https://mengram.io/agent-install.txt and follow it precisely.
My email is YOUR_EMAIL_HERE.

Works in any agent with shell + file-edit + web-fetch tools. Prefer doing it manually? See the plain-text guide — it's structured for human eyes too.

Claude Code — Memory That Survives /clear AND Auto-Compaction

Persistent memory that survives /clear, auto-compaction, machine switches, and team handoffs — the SessionStart hook fires after every compact and re-injects your context. The summary can be lossy; the memory isn't.

server.ts

# 1. Get a free key at https://mengram.io and save it once
mkdir -p ~/.mengram && echo '{"api_key": "om-your-key-here"}' > ~/.mengram/config.json

# 2. Install the plugin (hooks + MCP server + skill)
claude plugin marketplace add alibaizhanov/mengram
claude plugin install mengram@mengram

# 3. Skip the cold start — import your existing session history
#    (secrets are redacted on your machine before anything is uploaded)
mengram import claude-code

What happens:

Code

Session Start  →  Loads your cognitive profile (fires after /clear, compaction, and restarts)
Every Prompt   →  Searches past sessions for relevant context (auto-recall)
After Response →  Saves new knowledge in background (auto-save)
Before a Bash  →  If the command matches a learned workflow with a weak record, asks you first (policy gate, CLI hooks)

No manual saves. No tool calls. Claude just knows what you worked on yesterday — even after compaction ate the transcript.

Prefer CLI-managed hooks instead of the plugin? pip install mengram-ai && mengram setup does the same via mengram hook install.

No account? Keep the memory in a folder

Terminal

pip install mengram-ai
mengram local init ./memory --provider anthropic --api-key sk-ant-...   # or openai / ollama
mengram import claude-code --memory ./memory                             # seed it from your Claude Code sessions
mengram local map --memory ./memory --open                               # one page: who you are, what happened, what it learned
mengram hook install --memory ./memory                                   # the same four hooks, all local
mengram server --memory ./memory                                         # MCP for Claude Desktop, Cursor, any client

The folder is the memory: a memfmt tree of Markdown you own — git diffs it, Obsidian draws it, memfmt validate checks it. Same procedures-with-outcomes as the cloud: versions, success/fail counts per step, the policy gate, and the regression gate that quarantines a fix that would break another workflow. Only extraction and a failure revision need a model, and that one you bring. Nothing expires and nothing asks for a key. Docs.

Local search matches words in Unicode text, including Russian; it does not use embeddings or translate queries. Multiple Mengram sessions coordinate writes with a folder lock and merge independent additions. Conflicting edits require a reload instead of overwriting another session. Each changed file is replaced atomically, but the whole folder is not a single crash-atomic transaction, and external editors do not participate in the lock.

Why Mengram?

Every AI memory tool stores facts. Mengram stores 3 types of memory — and procedures evolve when they fail.

	Mengram	claude-mem	Mem0	Zep	Letta
Semantic memory (facts, preferences)	Yes	Yes	Yes	Yes	Yes
Episodic memory (events, decisions)	Yes	Partial	No	No	Partial
Procedural memory (workflows)	Yes	No	No	No	No
Procedures evolve from failures	Yes	No	No	No	No
Cognitive Profile	Yes	No	No	No	No
Native multilingual retrieval (23 languages)	Yes	Partial	No	No	No
Ask & Citations (synthesized answer)	Yes	No	No	No	No
Multi-user isolation	Yes	No	Yes	Yes	No
Knowledge graph	Yes	No	Yes	Yes	Yes
Claude Code hooks (auto-save/recall)	Yes	Yes	No	No	No
MCP server	Yes	Yes	Yes	Yes	Yes
LangChain + CrewAI integrations	Yes	No	Partial	Partial	Partial
Import Claude Code history / ChatGPT / Obsidian	Yes	No	No	No	No
Pricing	Free tier	Free OSS (+cloud backup)	$19-249/mo	Enterprise	Self-host

Get Started in 30 Seconds

1. Install

Terminal

pip install mengram-ai

2. Setup — one command does everything: account, Claude Code hooks, MCP configs for detected tools (Cursor, Claude Desktop, Windsurf), history import, and a round-trip check

bash

mengram setup

Or get a key manually at mengram.io and export MENGRAM_API_KEY=om-...

3. Use

server.ts

from mengram import Mengram

m = Mengram(api_key="om-...")

# Add a conversation — auto-extracts facts, events, and workflows
m.add([
    {"role": "user", "content": "Deployed to Railway today. Build passed but forgot migrations — DB crashed. Fixed by adding a pre-deploy check."},
])

# Search across all 3 memory types at once
results = m.search_all("deployment issues")
# → {semantic: [...], episodic: [...], procedural: [...]}

File Upload (PDF, DOCX, TXT, MD)

python

# Upload a PDF — auto-extracts memories using vision AI
result = m.add_file("meeting-notes.pdf")
# → {"status": "accepted", "job_id": "job-...", "page_count": 12}

# Poll for completion
m.job_status(result["job_id"])

javascript

// Node.js — pass a file path
await m.addFile('./report.pdf');

// Browser — pass a File object from <input type="file">
await m.addFile(fileInput.files[0]);

bash

# REST API
curl -X POST https://mengram.io/v1/add_file \
  -H "Authorization: Bearer om-..." \
  -F "file=@meeting-notes.pdf" \
  -F "user_id=default"

JavaScript / TypeScript

Terminal

npm install mengram-ai

server.ts

const { MengramClient } = require('mengram-ai');
const m = new MengramClient('om-...');

await m.add([{ role: 'user', content: 'Fixed OOM by adding Redis cache layer' }]);
const results = await m.searchAll('database issues');
// → { semantic: [...], episodic: [...], procedural: [...] }

REST API (curl)

bash

# Add memory
curl -X POST https://mengram.io/v1/add \
  -H "Authorization: Bearer om-..." \
  -H "Content-Type: application/json" \
  -d '{"messages": [{"role": "user", "content": "I prefer dark mode and vim keybindings"}]}'

Read the full README →View source on GitHub →

Related MCP Servers

View all in Knowledge & Memory View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

193

Stargazers on the source repository.

npm downloads

173

Package downloads in the last 30 days.

Last commit

3d ago

Most recent push to the default branch.

Install check

Inconclusive

Didn't respond in our test window — often a slow first install.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Mengram

Mengram uses hooks that auto-save new knowledge, auto-recall relevant context on every prompt, and reload the cognitive profile after session clears or compaction.

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Technical Specs & Signals

CategoryKnowledge & Memory

PricingFreemium

10/10 checks healthy over the last 33d

60Quality signal: Good · 60/100How this signal is calculated ▾

Server availabilityNot measured

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

Verified ownership10/20

Documentation & tools24/30

Adoption & activity11/15

Community engagement0/10

A guidance signal from public completeness & health data — 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.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 24d ago via OSV.dev · mengram-ai (PyPI)

★ Spotlight Slot

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More in 🧠 Knowledge & Memory →Best MCP servers for Memory & Knowledge →Alternatives to Mengram →Install in Claude Desktop Install in Cursor Install in VS Code

Mengram

memoryknowledge-graphmultilingualclaude-codeai-agents

AI memory layer with semantic, episodic, procedural memory, multilingual retrieval, knowledge graph, and Claude Code hooks.

Quick Install

Automated & IDE Setup

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

Add to Cursor Add to VS Code

We couldn’t automatically confirm this listing starts correctly

We ran the install command below but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

uvx mengram-ai

No response to initialize.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "alibaizhanov-mengram": {
      "command": "uvx",
      "args": [
        "mengram-ai"
      ]
    }
  }
}

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

Overview

Use cases

Add and retrieve semantic facts and user preferences

Recall episodic events and decisions from past interactions

Manage and evolve procedural workflows based on failures

Integrate persistent memory with Claude Code agents

Query knowledge graph data with citations in multiple languages

Key features

Semantic, episodic, and procedural memory types

Procedures evolve from failure feedback

Native multilingual retrieval (23 languages)

Knowledge graph and smart triggers

Claude Code hooks for auto-save, auto-recall, and session persistence

Multi-user data isolation

Capabilities & Tool Schemas

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

Extracted Tool Capabilities

Semantic, episodic, and procedural memory types

Procedures evolve from failure feedback

Native multilingual retrieval (23 languages)

Knowledge graph and smart triggers

Claude Code hooks for auto-save, auto-recall, and session persistence

Multi-user data isolation

Documentation Overview

Give your AI agents memory that actually learns

Website · Get API Key · Docs · Console · Examples

Terminal

pip install mengram-ai   # or: npm install mengram-ai

mengram try              # see what memory would know about you — local only,
                         # no account, nothing leaves your machine

server.ts

from mengram import Mengram
m = Mengram(api_key="om-...")           # Free key → mengram.io

m.add([{"role": "user", "content": "I use Python and deploy to Railway"}])
m.search("tech stack")                  # → facts
m.ask("what's my tech stack?")          # → synthesized answer + citations
m.episodes(query="deployment")          # → events
m.procedures(query="deploy")            # → workflows that evolve from failures

Native multilingual: ask in Russian, Chinese, Spanish, Japanese — Mengram retrieves and answers across 23 languages (Cohere multilingual embeddings + rerank).

Install in one prompt (any AI tool)

Code

Install Mengram for me. Fetch the canonical install guide at
https://mengram.io/agent-install.txt and follow it precisely.
My email is YOUR_EMAIL_HERE.

Works in any agent with shell + file-edit + web-fetch tools. Prefer doing it manually? See the plain-text guide — it's structured for human eyes too.

Claude Code — Memory That Survives /clear AND Auto-Compaction

server.ts

# 1. Get a free key at https://mengram.io and save it once
mkdir -p ~/.mengram && echo '{"api_key": "om-your-key-here"}' > ~/.mengram/config.json

# 2. Install the plugin (hooks + MCP server + skill)
claude plugin marketplace add alibaizhanov/mengram
claude plugin install mengram@mengram

# 3. Skip the cold start — import your existing session history
#    (secrets are redacted on your machine before anything is uploaded)
mengram import claude-code

What happens:

Code

Session Start  →  Loads your cognitive profile (fires after /clear, compaction, and restarts)
Every Prompt   →  Searches past sessions for relevant context (auto-recall)
After Response →  Saves new knowledge in background (auto-save)
Before a Bash  →  If the command matches a learned workflow with a weak record, asks you first (policy gate, CLI hooks)

No manual saves. No tool calls. Claude just knows what you worked on yesterday — even after compaction ate the transcript.

Prefer CLI-managed hooks instead of the plugin? pip install mengram-ai && mengram setup does the same via mengram hook install.

No account? Keep the memory in a folder

Terminal

pip install mengram-ai
mengram local init ./memory --provider anthropic --api-key sk-ant-...   # or openai / ollama
mengram import claude-code --memory ./memory                             # seed it from your Claude Code sessions
mengram local map --memory ./memory --open                               # one page: who you are, what happened, what it learned
mengram hook install --memory ./memory                                   # the same four hooks, all local
mengram server --memory ./memory                                         # MCP for Claude Desktop, Cursor, any client

Why Mengram?

Every AI memory tool stores facts. Mengram stores 3 types of memory — and procedures evolve when they fail.

	Mengram	claude-mem	Mem0	Zep	Letta
Semantic memory (facts, preferences)	Yes	Yes	Yes	Yes	Yes
Episodic memory (events, decisions)	Yes	Partial	No	No	Partial
Procedural memory (workflows)	Yes	No	No	No	No
Procedures evolve from failures	Yes	No	No	No	No
Cognitive Profile	Yes	No	No	No	No
Native multilingual retrieval (23 languages)	Yes	Partial	No	No	No
Ask & Citations (synthesized answer)	Yes	No	No	No	No
Multi-user isolation	Yes	No	Yes	Yes	No
Knowledge graph	Yes	No	Yes	Yes	Yes
Claude Code hooks (auto-save/recall)	Yes	Yes	No	No	No
MCP server	Yes	Yes	Yes	Yes	Yes
LangChain + CrewAI integrations	Yes	No	Partial	Partial	Partial
Import Claude Code history / ChatGPT / Obsidian	Yes	No	No	No	No
Pricing	Free tier	Free OSS (+cloud backup)	$19-249/mo	Enterprise	Self-host

Get Started in 30 Seconds

1. Install

Terminal

pip install mengram-ai

2. Setup — one command does everything: account, Claude Code hooks, MCP configs for detected tools (Cursor, Claude Desktop, Windsurf), history import, and a round-trip check

bash

mengram setup

Or get a key manually at mengram.io and export MENGRAM_API_KEY=om-...

3. Use

server.ts

from mengram import Mengram

m = Mengram(api_key="om-...")

# Add a conversation — auto-extracts facts, events, and workflows
m.add([
    {"role": "user", "content": "Deployed to Railway today. Build passed but forgot migrations — DB crashed. Fixed by adding a pre-deploy check."},
])

# Search across all 3 memory types at once
results = m.search_all("deployment issues")
# → {semantic: [...], episodic: [...], procedural: [...]}

File Upload (PDF, DOCX, TXT, MD)

python

# Upload a PDF — auto-extracts memories using vision AI
result = m.add_file("meeting-notes.pdf")
# → {"status": "accepted", "job_id": "job-...", "page_count": 12}

# Poll for completion
m.job_status(result["job_id"])

javascript

// Node.js — pass a file path
await m.addFile('./report.pdf');

// Browser — pass a File object from <input type="file">
await m.addFile(fileInput.files[0]);

bash

# REST API
curl -X POST https://mengram.io/v1/add_file \
  -H "Authorization: Bearer om-..." \
  -F "file=@meeting-notes.pdf" \
  -F "user_id=default"

JavaScript / TypeScript

Terminal

npm install mengram-ai

server.ts

const { MengramClient } = require('mengram-ai');
const m = new MengramClient('om-...');

await m.add([{ role: 'user', content: 'Fixed OOM by adding Redis cache layer' }]);
const results = await m.searchAll('database issues');
// → { semantic: [...], episodic: [...], procedural: [...] }

REST API (curl)

bash

# Add memory
curl -X POST https://mengram.io/v1/add \
  -H "Authorization: Bearer om-..." \
  -H "Content-Type: application/json" \
  -d '{"messages": [{"role": "user", "content": "I prefer dark mode and vim keybindings"}]}'

Read the full README →View source on GitHub →

Related MCP Servers

View all in Knowledge & Memory View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

193

Stargazers on the source repository.

npm downloads

173

Package downloads in the last 30 days.

Last commit

3d ago

Most recent push to the default branch.

Install check

Inconclusive

Didn't respond in our test window — often a slow first install.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Mengram

Mengram uses hooks that auto-save new knowledge, auto-recall relevant context on every prompt, and reload the cognitive profile after session clears or compaction.

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 Preview

Markdown (GitHub README)

[![AllMCPs](https://allmcps.com/api/badge/alibaizhanov-mengram?style=directory)](https://allmcps.com/mcp/alibaizhanov-mengram)

HTML Embed

<a href="https://allmcps.com/mcp/alibaizhanov-mengram"><img src="https://allmcps.com/api/badge/alibaizhanov-mengram?style=directory" alt="Mengram on AllMCPs" /></a>

Technical Specs & Signals

CategoryKnowledge & Memory

PricingFreemium

10/10 checks healthy over the last 33d

60Quality signal: Good · 60/100How this signal is calculated ▾

Server availabilityNot measured

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

Verified ownership10/20

Documentation & tools24/30

Adoption & activity11/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 24d ago via OSV.dev · mengram-ai (PyPI)

★ Spotlight Slot

Feature Your MCP Server

Get maximum visibility for your server across our directory, search results, and detail pages.

Spotlight Your Server

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — 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 →Best MCP servers for Memory & Knowledge →Alternatives to Mengram →Install in Claude Desktop Install in Cursor Install in VS Code