Contexta
Persistent memory and knowledge graph for AI assistants — keyword + vector + graph search.
Open source Repository Open in the app JSON README (API)
About
Persistent memory and knowledge graph for AI assistants — keyword + vector + graph search.
Details
- Kind
- MCP servers
- Topic
- AI, RAG & memory
- Publisher
- cc.contexta
- Origin
- official
- Category
- ferramentas
- Transport
- http
- Version
- 1.0.0
- Last push
- 2026-04-09T20:45:15Z
- Repository state
- ativo
- License
- MIT
- Added
- 2026-08-29 03:00:49
- Updated
- 2026-08-29 03:00:49
- Origin id
cc.contexta/contexta-mcp
README
<p align="center">
<img src="assets/logo.png" alt="Contexta" width="320" />
</p>
<h1 align="center">Contexta MCP</h1>
<p align="center">
<b>Persistent memory & knowledge graph for your AI assistant.</b><br/>
Keyword + vector + graph search in a single lookup.
</p>
<p align="center">
<a href="https://smithery.ai/servers/ai-jcce/mcp-contexta">
<img src="https://img.shields.io/badge/Smithery-published-2dd4bf?style=flat-square" alt="Smithery" />
</a>
<a href="https://contexta.cc">
<img src="https://img.shields.io/badge/contexta.cc-website-07080d?style=flat-square" alt="Website" />
</a>
<a href="LICENSE">
<img src="https://img.shields.io/badge/license-MIT-blue?style=flat-square" alt="License" />
</a>
</p>
---
## What is Contexta
Contexta is a memory MCP server that remembers like a human does — by meaning, by words, and by relationships.
Most memory tools give you one flavor of recall: embedding search, a raw log, or a graph you pay extra for. Contexta fuses all three into a single query. Your agent can ask _"what did we decide about pricing with Acme last quarter?"_ and get back the right meeting, the right decision, and the people connected to it — in one round-trip.
Under the hood, Contexta indexes your notes, messages, and documents as **typed entities** (people, projects, decisions, meetings, tasks) and links them into a knowledge graph automatically. Every retrieval combines:
- **Keyword search** — exact phrases, names, IDs
- **Vector search** — semantic meaning across languages
- **Graph traversal** — follow relationships between entities
## Why Contexta
- **Typed entities out of the box** — people, projects, decisions, meetings, tasks are first-class, not blobs of text
- **Knowledge graph included** — no paid tier gate on the graph layer
- **Triple retrieval in one call** — no need to stitch together three different memory APIs
- **30-second setup** — install via Smithery, sign in with OAuth, done
- **Per-user OAuth** — your memory is private; the server authenticates every request individually
- **Multilingual** — English and Russian equally supported
## Use cases
- Persistent memory for Claude, ChatGPT, and Cursor across sessions
- Long-term context for AI agents working on ongoing projects
- Personal knowledge base that actually understands who and what you mean
- Research and meeting recall without manually tagging anything
## Install
### Via Smithery (recommended)
One-click install from the [Smithery listing](https://smithery.ai/servers/ai-jcce/mcp-contexta) — Smithery handles the OAuth flow and proxies connections through its gateway.
### Manual — Claude Desktop
Add to your Claude Desktop config (`~/Library/Application Support/Claude/claude_desktop_config.json` on macOS, `%APPDATA%\Claude\claude_desktop_config.json` on Windows):
```json
{
"mcpServers": {
"contexta": {
"url": "https://mcp.contexta.cc/mcp"
}
}
}
```
Claude will walk you through the OAuth sign-in on first use. See [examples/claude-desktop.json](examples/claude-desktop.json).
### Manual — Cursor
Add a new MCP server in Cursor → Settings → MCP:
- **Name:** Contexta
- **Transport:** HTTP
- **URL:** `https://mcp.contexta.cc/mcp`
See [examples/cursor.json](examples/cursor.json).
### Manual — ChatGPT
In ChatGPT → Settings → Connectors → Add custom connector → paste `https://mcp.contexta.cc/mcp`. See [examples/chatgpt.md](examples/chatgpt.md) for full instructions.
## Authentication
Contexta uses **OAuth 2.0 with dynamic client registration** (RFC 7591) and PKCE. On first connection, your MCP client opens a browser window, you sign in with your Contexta account, and the client receives a per-user access token. Tokens are refreshed automatically.
No API keys, no shared credentials — every request runs as a specific user with that user's private memory.
## Tools exposed
Contexta MCP exposes the following tools to your AI client (non-exhaustive):
- `search` — keyword + vector + graph search across your memory
- `read_page` — fetch a note or document by ID
- `create_page` — save a new memory
- `update_page` — edit an existing memory
- `graph_search` — traverse the knowledge graph
- `list_tasks` / `create_task` / `update_task` — task management
- `list_workspaces` — available workspaces
- and more — the full tool list is discovered automatically by your MCP client.
## Links
- **Website:** [contexta.cc](https://contexta.cc)
- **App:** [app.contexta.cc](https://app.contexta.cc)
- **Smithery:** [smithery.ai/servers/ai-jcce/mcp-contexta](https://smithery.ai/servers/ai-jcce/mcp-contexta)
- **MCP endpoint:** `https://mcp.contexta.cc/mcp`
## License
MIT — see [LICENSE](LICENSE).
This repository is a public showcase for the hosted Contexta MCP service. The service itself is operated by the Contexta team at `mcp.contexta.cc`.