Engram
@ayvazyan10
About Engram
Persistent AI memory backend with semantic search and knowledge graph.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"engram": {
"command": "npx",
"args": [
"-y",
"@engram-ai-memory/mcp@latest"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Engram?
Engram is a universal AI memory backend that gives any AI model a persistent, growing brain. It stores memories in a local SQLite database with full-text search, vector semantic search, and a knowledge graph that connects related concepts.
How to use Engram?
Install the server with npx -y @engram-ai-memory/mcp@latest. Configure it as an MCP server in any compatible client such as Claude Desktop by adding the command and arguments to the mcpServers section of your client’s configuration.
Key features of Engram
- Semantic search finds memories by meaning, not just keywords
- 7-step knowledge graph traversal connects related memories
- Contradiction detection automatically flags conflicting beliefs
- Local-first – all embeddings run on-device, no API keys needed
- Universal – works with Claude, OpenAI, Ollama, and any MCP client
- 18 built-in MCP tools for memory management
Use cases of Engram
- Storing and retrieving past conversations, decisions, and events (episodic memory)
- Maintaining a persistent knowledge base of facts and beliefs (semantic memory)
- Recording how-to instructions, workflows, and code patterns (procedural memory)
- Detecting and resolving contradictory information in an AI’s knowledge base
- Providing long-term context to AI models across sessions and clients
FAQ from Engram
What types of memory does Engram support?
Engram supports three memory types: episodic (past events and conversations), semantic (facts and beliefs), and procedural (how-to instructions and workflows).
Does Engram require API keys or cloud services?
No. Engram is local-first – all embedding and search run on-device, and no data leaves your machine. No API keys are needed.
Which AI clients can use Engram?
Engram works with Claude, OpenAI, Ollama, and any MCP-compatible client.
Where are memories stored?
Memories are stored in a local SQLite database on your machine.
What MCP tools does Engram provide?
Engram offers 18 tools, including store_memory, search_memory, recall_context, add_knowledge, check_contradictions, resolve_contradiction, forget, tag_memory, list_tags, decay_sweep, decay_policy, re_embed, embedding_status, index_status, memory_stats, plugin_list, webhook_subscribe, and webhook_list.
Frequently asked questions
What types of memory does Engram support?
Engram supports three memory types: episodic (past events and conversations), semantic (facts and beliefs), and procedural (how-to instructions and workflows).
Does Engram require API keys or cloud services?
No. Engram is local-first – all embedding and search run on-device, and no data leaves your machine. No API keys are needed.
Which AI clients can use Engram?
Engram works with Claude, OpenAI, Ollama, and any MCP-compatible client.
Where are memories stored?
Memories are stored in a local SQLite database on your machine.
What MCP tools does Engram provide?
Engram offers 18 tools, including `store_memory`, `search_memory`, `recall_context`, `add_knowledge`, `check_contradictions`, `resolve_contradiction`, `forget`, `tag_memory`, `list_tags`, `decay_sweep`, `decay_policy`, `re_embed`, `embedding_status`, `index_status`, `memory_stats`, `plugin_list`, `webhook_subscribe`, and `webhook_list`.
Basic information
More Memory & Knowledge MCP servers
Anytype MCP Server
anyprotoAn MCP server enabling AI assistants to interact with Anytype - your encrypted, local and collaborative wiki - to organize objects, lists, and more through natural language.
Obsidian MCP Server
cyanheadsRead, write, search, and surgically edit Obsidian vault notes, tags, and frontmatter via MCP. STDIO or Streamable HTTP.
Jupyter Notebook MCP Server (for Cursor)
jbenoModel Context Protocol (MCP) server designed to allow AI agents within Cursor to interact with Jupyter Notebook (.ipynb) files

Dash Api Docs Mcp Server
KapeliMCP server for Dash, the macOS API documentation browser
Zettelkasten MCP Server
entanglrA Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology, allowing you to create, link, explore and synthesize atomic notes through Claude and other MCP-compatible clients.
Comments