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solucortex-mcp
Advanced tools
Official Model Context Protocol server for SoluCortex — 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 ·
Setup guide: solucortex.ai/docs/mcp ·
Tools reference: solucortex.ai/docs/mcp-tools ·
PyPI: solucortex-mcp ·
MCP Registry: io.github.soluai-spa/solucortex-mcp

| 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_update_memory | Corrects an existing memory — the edit returns it to pending for human re-approval in the panel | When a memory is right in spirit but wrong in detail |
solucortex_flag_memory | Flags a memory as outdated/incorrect with a reason; a human resolves it in the panel | When a memory should be reviewed, archived or deleted |
solucortex_list_memories | Lists memories without semantic search | Quick inspection / audit |
Governance by design: agents propose, humans govern. Agents can never change a memory's
status, rewrite its metadata, or delete it — edits go back to pending and deletions only happen from the SoluCortex panel.
scx_) — get it from your
SoluCortex dashboard.uv (recommended), Python ≥ 3.10, or Docker.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 |
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).
The hosted server at https://mcp.solucortex.ai/mcp speaks Streamable HTTP; your key
travels with each request:
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:
{
"mcpServers": {
"solucortex": {
"type": "http",
"url": "https://mcp.solucortex.ai/mcp",
"headers": {
"Authorization": "Bearer scx_xxx",
"X-Solucortex-Project": "your-project-uuid"
}
}
}
}
claude mcp add solucortex \
-e SOLUCORTEX_API_KEY=scx_xxx \
-e SOLUCORTEX_PROJECT_ID=your-project-uuid \
-- uvx solucortex-mcp
Add to the client's MCP config (claude_desktop_config.json, Cursor mcp.json, etc.):
{
"mcpServers": {
"solucortex": {
"command": "uvx",
"args": ["solucortex-mcp"],
"env": {
"SOLUCORTEX_API_KEY": "scx_xxx",
"SOLUCORTEX_PROJECT_ID": "your-project-uuid"
}
}
}
}
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
Prebuilt image on GHCR:
docker run --rm -i \
-e SOLUCORTEX_API_KEY=scx_xxx \
ghcr.io/soluai-spa/solucortex-mcp:latest
Or build it yourself:
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).
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
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.MIT — see LICENSE.
FAQs
Official MCP server for SoluCortex — living technical memory for AI agents.
We found that solucortex-mcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.

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