solucortex-mcp

# SoluCortex MCP

<!-- mcp-name: io.github.soluai-spa/solucortex-mcp -->

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Official [Model Context Protocol](https://modelcontextprotocol.io) server for
**[SoluCortex](https://solucortex.ai)** — living technical memory for AI agents.

Connect any MCP-compatible agent (Claude Code, Claude Desktop, Cursor, Codex, Cline, …) to
your SoluCortex project so it can **recall** the decisions, conventions, risks and architecture
that matter before it works, and **remember** what it learns when it's done.

**Website:** [solucortex.ai](https://solucortex.ai) ·
**Setup guide:** [solucortex.ai/docs/mcp](https://solucortex.ai/docs/mcp) ·
**Tools reference:** [solucortex.ai/docs/mcp-tools](https://solucortex.ai/docs/mcp-tools) ·
**PyPI:** [solucortex-mcp](https://pypi.org/project/solucortex-mcp/) ·
**MCP Registry:** `io.github.soluai-spa/solucortex-mcp`

<p align="center"><img src="docs/demo.gif" alt="SoluCortex MCP demo: recall approved context at task start, remember learnings at close" width="760"></p>

## Tools

| Tool | What it does | When to use |
|------|--------------|-------------|
| `solucortex_recall` | Builds living context for a task (ranked by semantic similarity + importance) | At the **start** of a task, before touching code |
| `solucortex_search` | Ad-hoc semantic search over the project's memories | Specific questions mid-task |
| `solucortex_remember` | Records a memory (stored `approved` + traced as an authorized agent) | At **close**, or on a relevant technical decision |
| `solucortex_list_memories` | Lists memories without semantic search | Quick inspection / audit |

## Requirements

- A SoluCortex account and a **project API key** (prefix `scx_`) — get it from your
  [SoluCortex dashboard](https://solucortex.ai).
- One of: [`uv`](https://docs.astral.sh/uv/) (recommended), Python ≥ 3.10, or Docker.

## Configuration

### stdio mode (default, local)

The server is configured entirely through environment variables:

| Variable | Required | Description |
|----------|----------|-------------|
| `SOLUCORTEX_API_KEY` | ✅ | Project API key (`scx_…`) |
| `SOLUCORTEX_PROJECT_ID` | optional | Default project UUID; if omitted, the backend infers it from the API key |
| `SOLUCORTEX_URL` | optional | API base URL. Default `https://solucortex.ai` |

### HTTP mode (remote, multi-tenant)

Run with `MCP_TRANSPORT=http` (or `--http`) to serve Streamable HTTP on `$PORT`
(default 8080) — the mode behind `https://mcp.solucortex.ai`. Credentials travel with
**each request** and the environment is ignored:

| Header | Required | Description |
|--------|----------|-------------|
| `Authorization: Bearer scx_…` | ✅ | The caller's project API key (401 without it) |
| `X-Solucortex-Project` | optional | Default project UUID; if omitted, the backend infers it from the API key |

`GET /health` (and `/healthz` locally; Cloud Run's frontend intercepts `/healthz`) responds without auth. The MCP endpoint is
`/mcp`, runs stateless, and shares nothing between requests/tenants.

Never commit your API key. Keep it in your MCP client config's `env` block or a local `.env`
(see [`.env.example`](.env.example)).

## Install

### Remote (recommended — nothing to install)

The hosted server at `https://mcp.solucortex.ai/mcp` speaks Streamable HTTP; your key
travels with each request:

```bash
claude mcp add --transport http solucortex https://mcp.solucortex.ai/mcp \
  --header "Authorization: Bearer scx_xxx" \
  --header "X-Solucortex-Project: your-project-uuid"
```

Or in any client with remote MCP support:

```json
{
  "mcpServers": {
    "solucortex": {
      "type": "http",
      "url": "https://mcp.solucortex.ai/mcp",
      "headers": {
        "Authorization": "Bearer scx_xxx",
        "X-Solucortex-Project": "your-project-uuid"
      }
    }
  }
}
```

### Claude Code (local, stdio)

```bash
claude mcp add solucortex \
  -e SOLUCORTEX_API_KEY=scx_xxx \
  -e SOLUCORTEX_PROJECT_ID=your-project-uuid \
  -- uvx solucortex-mcp
```

### Claude Desktop / Cursor / Cline (JSON config)

Add to the client's MCP config (`claude_desktop_config.json`, Cursor `mcp.json`, etc.):

```json
{
  "mcpServers": {
    "solucortex": {
      "command": "uvx",
      "args": ["solucortex-mcp"],
      "env": {
        "SOLUCORTEX_API_KEY": "scx_xxx",
        "SOLUCORTEX_PROJECT_ID": "your-project-uuid"
      }
    }
  }
}
```

### From a local clone

```bash
git clone https://github.com/soluai-spa/solucortex-mcp
cd solucortex-mcp
cp .env.example .env   # fill in your key
./run.sh               # loads .env, then runs via uv
# or, with SOLUCORTEX_* already exported: uv run solucortex-mcp
```

### Docker

```bash
docker build -t solucortex-mcp .
docker run --rm -i \
  -e SOLUCORTEX_API_KEY=scx_xxx \
  -e SOLUCORTEX_PROJECT_ID=your-project-uuid \
  solucortex-mcp
```

The server speaks MCP over **stdio**, so clients launch it as a subprocess (`-i` keeps stdin open).

## Development

```bash
uv sync
uv run solucortex-mcp            # run (stdio)
MCP_TRANSPORT=http uv run solucortex-mcp   # run (HTTP on :8080)
uv run pytest                    # test suite
npx @modelcontextprotocol/inspector uv run solucortex-mcp   # interactive test
```

## Notes

- Memory `type` vocabulary: the canonical set is `architecture, decision, risk, convention,
  bug_history, tech_debt, sensitive_module, learning, external_integration`. Some backends
  accept an older set (`technical_decision, historical_bug, current_state, task_closure`).
  The server passes `type` through and surfaces `HTTP 422` so you can retry with the other set.
- Never store real secrets in a memory. Record location, type, severity and action taken instead.

## License

MIT — see [LICENSE](LICENSE).