io.github.soluai-spa由 GitHub 帳號 soluai-spa 發布v1.1.2更新於 Oct 24, 2026
Living technical memory for AI agents: recall approved project context, record what was learned.
SoluCortex MCP 為助理提供專案的「活技術記憶」：取回已核准的決策、慣例與風險，並記錄任務中學到的內容。
Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.soluai-spa%2Fsolucortex-mcp/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"solucortex": {
"type": "http",
"url": "https://mcp.solucortex.ai/mcp",
"headers": {
"Authorization": "Bearer <YOUR_TOKEN>"
}
}
}
}[PyPI] [CI] [Python] [License: MIT]
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
[SoluCortex MCP demo: recall approved context at task start, remember learnings at close]
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:
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:
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:
Or in any client with remote MCP support:
Add to the client's MCP config (claude_desktop_config.json, Cursor mcp.json, etc.):
Prebuilt image on GHCR:
Or build it yourself:
The server speaks MCP over stdio, so clients launch it as a subprocess (-i keeps stdin open).
Once connected, give your agent the methodology too: copy
templates/AGENTS.md into the root of your repo (it works as
AGENTS.md or CLAUDE.md). The MCP handshake already carries these instructions — the
file lets you version them alongside your code, extend them with your own conventions,
and optionally enable the commented Claude Code hook recipe for guaranteed recall.
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.
來源：README.md，提交 b97a3af
SoluCortex: recall task context
Build living context for a task (POST /context/build). Call this at the START of a task, before touching code: returns approved, active memories (decisions, conventions, risks, sensitive modules, architecture) ranked by semantic similarity + importance. Uses OpenAI embeddings (slower, 20 req/min).
query必填project_idSoluCortex: semantic memory search
Ad-hoc semantic search of memories (POST /search/semantic). Use for specific questions during a task (e.g. 'how is authentication implemented?'), distinct from recall which builds the full startup context. Uses OpenAI embeddings (20 req/min).
limitquery必填project_idSoluCortex: record a memory
Record a memory in SoluCortex (POST /memories). Call when closing a task or making a relevant technical decision. As an authorized agent (Bearer api_key), the memory is stored with status 'approved' and traced. Never store real secrets: if you find one, record location/type/severity and action taken, with a redacted reference.
type必填title必填content必填importanceproject_idSoluCortex: update a memory (requires human re-approval)
Correct an existing memory (PATCH /memories/{id}). Agents propose, humans govern: the edit is applied but the memory returns to PENDING until a human re-approves it. ALWAYS tell the user the change awaits their approval in the SoluCortex panel. Status changes are not possible here.
typetitlecontentmemory_id必填importanceSoluCortex: flag a memory for human review
Flag a memory as outdated/incorrect (POST /memories/{id}/flag). The memory is marked for human review in the SoluCortex panel; nothing is deleted or unpublished. ALWAYS tell the user a memory awaits their decision in the panel. Deletion is human-only by design.
reason必填memory_id必填suggested_actionSoluCortex: list memories
List the project's memories without semantic search (GET /memories). Useful for quick inspection/audit or to confirm a just-created memory was stored. Does not consume OpenAI quota.
limitproject_id已滿足適用檢查項的 100%
該評分衡量此收錄條目的完整程度，依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價，也不表示伺服器安全或目前可用：可連通性是帶日期的檢查結果，評分也不包含安裝量或使用者評價。
claude mcp add --transport http solucortex https://mcp.solucortex.ai/mcp \ --header "Authorization: Bearer scx_xxx" \ --header "X-Solucortex-Project: your-project-uuid"{ "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{ "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-mcpcd solucortex-mcpcp .env.example .env # fill in your key./run.sh # loads .env, then runs via uv# or, with SOLUCORTEX_* already exported: uv run solucortex-mcpdocker run --rm -i \ -e SOLUCORTEX_API_KEY=scx_xxx \ ghcr.io/soluai-spa/solucortex-mcp:latestdocker build -t solucortex-mcp .docker run --rm -i \ -e SOLUCORTEX_API_KEY=scx_xxx \ -e SOLUCORTEX_PROJECT_ID=your-project-uuid \ solucortex-mcpuv syncuv run solucortex-mcp # run (stdio)MCP_TRANSPORT=http uv run solucortex-mcp # run (HTTP on :8080)uv run pytest # test suitenpx @modelcontextprotocol/inspector uv run solucortex-mcp # interactive test