uctx
A local, user-owned memory MCP server that allows AI agents to share context via a SQLite file you own.
README
uctx — your context, not the vendor's
A local, user-owned memory that you fill once and every AI agent can read.
Today each assistant keeps its own siloed memory. Tell Claude you prefer Python;
ChatGPT still has no idea. uctx is a tiny MCP
server backed by a local SQLite file you own — so the same context is
readable and writable by any MCP-enabled agent (Claude Desktop, Cursor, …).
No cloud. No account. The data is a file on your machine (~/.uctx/context.db).
Claude Desktop ┐
├──► uctx (MCP server) ──► ~/.uctx/context.db ← you own this
Cursor ┘
The 30-second demo
- In Claude Desktop: "Remember that I prefer Python, tabs over spaces, and I'm learning agentic frameworks."
→ it calls
save_context. - In Cursor (or a fresh Claude chat): "What do you know about my coding preferences?"
→ it calls
search_contextand answers correctly.
Two different agents, one shared memory you control. That's the whole idea.
Or run the demo right now (no agent setup)
uv sync
uv run python examples/two_agents_demo.py
Agent A = 'claude-desktop' — saves what the user tells it:
[claude-desktop] save_context('Prefers Python, tabs over spaces') -> Saved context #1
[claude-desktop] save_context('Based in Boston') -> Saved context #2
[claude-desktop] save_context('Learning agentic frameworks') -> Saved context #3
---- Switch apps. Brand-new agent, same local store, no shared chat. ----
Agent B = 'cursor' — recalls it without ever seeing the above:
[cursor] search_context('coding')
-> #1 [preference] Prefers Python, tabs over spaces ·tags: coding style ·from claude-desktop
=> Two different agents. One context you own.
Two separate MCP clients, one local store — the cross-app share, proven in one command.
Install (two commands)
Requires uv (Python 3.10+).
uv tool install git+https://github.com/tmeng7777/uctx.git # installs the `uctx` command
uctx setup # auto-wire Claude Desktop + Cursor
uctx setup detects your MCP clients, backs up their configs, and adds the uctx
server — no hand-editing JSON. Then restart the app(s) to load the tools.
Just want to try it without installing? uvx --from git+https://github.com/tmeng7777/uctx.git uctx web.
The uctx command:
uctx run the MCP server (what your agents call)
uctx setup [claude|cursor] wire uctx into your AI clients
uctx web open the local dashboard
uctx sync [set|pull|push] sync your context across devices
Manual config (fallback)
If you'd rather edit JSON, add this to Claude Desktop's claude_desktop_config.json
(Settings → Developer → Edit Config) or Cursor's ~/.cursor/mcp.json:
{ "mcpServers": { "uctx": { "command": "uctx", "args": [] } } }
Web UI — see & manage your context
A local dashboard for the same store your agents use — view, search, add, edit, and delete anything, so you can see what's been remembered about you (and change what shouldn't be).
uv run uctx-web # then open http://127.0.0.1:8787
Reads/writes the same ~/.uctx/context.db. Localhost-only, single-user.
Sync — your context on every device (you own the file)
Point uctx at a folder your own cloud already syncs (Dropbox, iCloud Drive, Google Drive) or a git repo. Your context travels with you — and you hold the file, not a uctx server.
uctx-sync set ~/Dropbox/uctx # once, per machine
uctx-sync # pull others' changes in, push yours out
Each machine keeps its own fast local SQLite store and shares a portable
context.jsonl snapshot through the folder. (We sync JSONL, not the raw
.db, because cloud tools corrupt live SQLite files — this stays safe,
human-readable, and git-diffable.)
v0 limitation: sync is additive/union and dedupes by content — edits and deletes don't propagate yet. That needs stable per-item UUIDs + tombstones (roadmap). Encryption of the synced file (so the provider can't read it) is the planned next step.
Tools
| Tool | What it does |
|---|---|
save_context(content, type, tags, source_app) |
Remember a preference / fact / note |
search_context(query, limit) |
Keyword-search saved context |
list_context(limit) |
List everything, most recent first |
forget_context(item_id) |
Delete one item |
The v0 schema (small on purpose)
{
"id": 1,
"type": "preference | fact | note",
"content": "Prefers Python, tabs over spaces",
"tags": "coding style",
"source_app": "claude-desktop",
"created_at": "2026-07-19T..."
}
source_app + created_at are the seed of provenance — so trust and
versioning can be added later without a migration.
Deliberately NOT in v0 (the roadmap)
These are the genuinely hard parts, and they come only if people actually use v0:
- Semantic search (embeddings) instead of keyword
LIKE - Provenance / signing — verify who wrote a memory
- Temporal validity — facts that expire or get superseded
- Access control — per-app read/write scopes, revocation
- Multi-user / identity
Why local-first
Portable, user-owned context is something the big labs are structurally
disinclined to build — your memory is their lock-in. uctx keeps the data in a
file you own, and moves it between vendors instead of trapping it inside one.
Status
Early prototype. Built to find out one thing: does anyone actually reach for this once the novelty wears off? If that's you — open an issue and tell me what you'd want next.
MIT licensed.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.