engram-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@engram-mcpsearch for architecture overview in my workspace"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
engram-mcp
MCP plugin that connects Cursor, Claude Code, Claude Desktop, and any other MCP-speaking host to your Engram workspace — the indexed knowledge of your GitHub repos and Notion pages.
The plugin is a thin client: no local database, no embedding model, no vector store. It forwards tool calls to the Engram backend over HTTPS and renders the results for your LLM.
Install
pip install engram-mcp
# or
uv tool install engram-mcpRelated MCP server: PLUR
Configure your MCP client
You need two things:
Your Engram backend URL —
https://your-engram.example.comin production, orhttp://localhost:8000for local development.An Engram MCP token — mint one from your Engram web app under Settings → MCP Tokens. Tokens are scoped to your user and expire after 90 days.
Claude Desktop / Claude Code
Add to claude_desktop_config.json (or the equivalent Claude Code
config):
{
"mcpServers": {
"engram": {
"command": "engram-mcp",
"env": {
"ENGRAM_BASE_URL": "https://your-engram.example.com",
"ENGRAM_TOKEN": "eng_mcp_..."
}
}
}
}Cursor
In Cursor settings → MCP → Add new server:
{
"engram": {
"command": "engram-mcp",
"env": {
"ENGRAM_BASE_URL": "https://your-engram.example.com",
"ENGRAM_TOKEN": "eng_mcp_..."
}
}
}Codex CLI
# ~/.codex/config.toml
[mcp_servers.engram]
command = "engram-mcp"
env = { ENGRAM_BASE_URL = "https://your-engram.example.com", ENGRAM_TOKEN = "eng_mcp_..." }Tools exposed
Tool | What it does |
| Ranked search across your indexed GitHub + Notion content. Supports |
| Locators only (source, path, line range, URL) for an answer the LLM has already drafted — cheap on context. |
| Full document fetch by id, optionally with surrounding context lines. Use after |
How it works
┌───────────────────┐ stdio MCP ┌───────────────────┐ HTTPS ┌──────────────────┐
│ Cursor / Claude │ ───────────► │ engram-mcp │ ───────► │ Engram backend │
│ Code / Desktop │ │ (this package) │ bearer │ (indexing, RAG, │
└───────────────────┘ └───────────────────┘ token │ cross-val) │
└──────────────────┘The plugin holds no state. Your token authenticates each request to the Engram backend, which resolves it to your user + workspace, runs retrieval against the indexed corpus, and returns ranked chunks. The plugin formats those chunks as markdown for the host LLM.
Auth
v0.x uses paste tokens — generate one in the Engram web app,
paste into the env var. Tokens are stored hashed server-side and you
can revoke them from the same settings page.
v1.x will add OAuth 2.1 (device flow + Dynamic Client
Registration) so you can add Engram as a claude.ai connector with
zero copy-paste. Paste tokens will keep working.
Development
git clone https://github.com/hidden-ones-dev/engram-mcp
cd engram-mcp
pip install -e ".[dev]"
pytestPoint at a local Engram backend:
export ENGRAM_BASE_URL=http://localhost:8000
export ENGRAM_TOKEN=eng_mcp_...
python -m engram_mcp # speaks stdio MCP; pipe from a host or test harnessLicense
MIT — see LICENSE.
Related
Engram — the backend this plugin talks to.
Model Context Protocol — the protocol spec.
This server cannot be deployed
Maintenance
Related MCP Connectors
MCP-native notes and memory for ChatGPT, Claude, and other AI tools.
Shared memory and actions for Claude, Kiro, OpenAI, Cursor, and other MCP-compatible AI clients.
Search GitHub, npm, PyPI, StackOverflow, ArXiv from one MCP — built for coding agents.
Hosted MCP memory: save sessions/decisions once, search from Claude, Cursor, ChatGPT. EU-hosted FTS.
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