Msty Admin
M-Pineapple14 ดาว
AI-powered administration for Msty Studio Desktop. 56 MCP tools for database insights, config sync, local model orchestration, and Claude handoff workflows.
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เปิดComprehensive MCP server for administering Msty Studio Desktop 2.9+ with 56 tools across 9 phases: real Studio path/DB detection, entity inventory (Context Studio, Knowledge Stacks, Agent Mode, Turnstiles, …), insights analytics, Nexus bridge, Bloom evaluation, multi-backend local inference, and a handoff from a local model to the Cursor agent on this Mac.
Requirements: Python 3.10+, MCP SDK v1.0.0+, psutil 5.9.0+
macOS ships python3 3.9. This package will not install on that interpreter. Use Homebrew Python 3.12 (or any 3.10+) as shown below.
New to Bloom? Jump to the Bloom Behavioral Evaluation section or read the full Bloom guide.
Python 3.10 or newer is required. On macOS the system python3 is 3.9, so create the venv with Homebrew Python:
brew install [email protected]
python3.12 -m venv .venv
source .venv/bin/activate
pip install msty-admin-mcp
msty-admin-mcp # Runs on stdio (default MCP transport)
If you already have Python 3.10+ as python3, python3 -m venv .venv is enough. Then pip install msty-admin-mcp as above.
If pip install msty-admin-mcp cannot find the package, install the release straight from GitHub:
pip install "msty-admin-mcp @ git+https://github.com/M-Pineapple/[email protected]"
pip install "msty-admin-mcp[http]"
msty-admin-mcp --transport streamable-http # Runs on http://localhost:8000
git clone https://github.com/M-Pineapple/msty-admin-mcp
cd msty-admin-mcp
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[test]"
pytest tests/ -v
This server targets the 1.x MCP Python SDK (mcp>=1.0.0,<2).
After pip install msty-admin-mcp, the console script msty-admin-mcp is on that environment's PATH. Point the host at it.
Claude Desktop — merge into ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"msty-admin": {
"command": "msty-admin-mcp"
}
}
}
Cursor — merge into ~/.cursor/mcp.json:
{
"mcpServers": {
"msty-admin": {
"command": "msty-admin-mcp"
}
}
}
If the host cannot see the script, set command to the absolute path of msty-admin-mcp inside the venv (…/bin/msty-admin-mcp). Restart the host after editing.
The Frontier one-tool server is separate. See Hybrid local model and Cursor agent.
Once the server is registered with Msty Studio (or another MCP host), ask in natural language. The host maps your words onto the tools.
For a local-model chat, use the one-tool Frontier server (see Hybrid local model and Cursor agent):
Environment variables (all optional, sensible defaults):
# Msty installation host
MSTY_HOST=127.0.0.1
# Service backend ports (also read from Studio Gifnoc.nosj when present)
MSTY_AI_PORT=11964 # Local AI (Ollama)
MSTY_MLX_PORT=11973 # MLX service
MSTY_LLAMACPP_PORT=11454 # LLaMA.cpp service
MSTY_VIBE_PORT=8317 # Vibe CLI Proxy
MSTY_NEXUS_PORT=11434 # Msty Nexus OpenAI-compatible gateway
# Service timeout
MSTY_TIMEOUT=10 # Seconds
# Bloom integration (required for Phase 6 tools)
ANTHROPIC_API_KEY=sk-... # Required for Bloom judge model
Msty Studio no longer uses a top-level msty.db. The workspace SQLite lives under the Chromium File System API path, for example:
~/Library/Application Support/MstyStudio/
├── Gifnoc.nosj # service config (ports / model paths)
├── models/ models-mlx/
└── File System/000/t/00/00000000 # Drizzle SQLite workspace DB
The MCP auto-detects /Applications/MstyStudio.app, reads the bundle version, resolves the SQLite blob, and opens it read-only.
Msty Studio Desktop
├── Local AI (Ollama) → port 11964
├── MLX → port 11973
├── LLaMA.cpp → port 11454
├── Vibe CLI Proxy → port 8317
└── Msty Nexus (optional) → port 11434
↓
MCP Server (stdio / HTTP)
├── Phase 1: Foundational (6)
├── Phase 2: Configuration (4)
├── Phase 3: Service Integration (11)
├── Phase 4: Intelligence (5)
├── Phase 5: Calibration (4)
├── Phase 6: Bloom Evaluation (6)
├── Phase 7: Studio Inventory (15)
├── Phase 8: Nexus Bridge (4)
└── Phase 9: Frontier handoff (1)
A local model does the ordinary work. When a question is past it, that model calls ask_frontier. The tool runs the Cursor agent on this machine and returns the answer in the same Msty chat. A follow-up resumes that Cursor chat.
Use a separate one-tool server for the local-model chat. The full admin server has 56 tools. A small model will call those other tools (GitHub, search, schema, and so on) instead of waiting for the answer.
cursor-agent). It must be on the PATH seen by Msty, or at ~/.local/bin/cursor-agent. Login and API keys: Cursor CLI authentication.{
"command": "/absolute/path/to/venv/bin/python",
"args": ["-m", "src.frontier_main"],
"env": {
"PYTHONPATH": "/absolute/path/to/msty-admin-mcp",
"CURSOR_API_KEY": "your-user-api-key"
}
}
After pip install, the console script msty-frontier is the same one-tool server. You can set command to that script and omit PYTHONPATH.
ask_frontier card, then the Cursor reply under it. A normal paragraph with no card means the model answered by itself and Cursor was not asked.By default the Cursor agent reads an empty folder under ~/.msty-admin/frontier-workspace. It cannot see your repositories. To let it read one project, set:
"MSTY_FRONTIER_WORKSPACE": "/absolute/path/to/that/project"
Ask mode does not send mail, move or delete files, or use trading tools. It can read that folder.
The admin server is unchanged for Studio inventory and the other 55 tools. Add the Frontier server and the one-server toolset as above. Do not point the local-model chat at the full msty-admin-mcp command.
ask_frontier and the text under it came from Cursor.cursor-agent status can say "not logged in" while ask mode still works with CURSOR_API_KEY. The frontier process passes that variable as --api-key. A browser cursor-agent login in your terminal is not always visible to the process Msty starts.ask_frontier calls in one reply share the first Cursor answer. They do not each start a new chat.~/.msty-admin/frontier-session.json (mode 0600). Delete that file to start a fresh Cursor chat.identify_handoff_triggers only scores past speed and latency. It does not send the question.detect_msty_installation — app, version, DB path, portsread_msty_database — stats / tables / read-only SQL
list_configured_tools — Toolbox MCP toolsget_model_providers — services + Studio providers (keys redacted)analyse_msty_health — install + DB + servicesget_server_status — MCP statusexport_tool_config — export a tool by name/idsync_claude_preferences — Claude ↔ Msty delta reportgenerate_persona — persona JSON for Persona Studioimport_tool_config — validate import (live DB writes refused by default)get_service_status, list_available_models, query_local_ai_servicechat_with_local_model, recommend_modellist_mlx_models, chat_with_mlx_modellist_llamacpp_models, chat_with_llamacpp_modelget_vibe_proxy_status, query_vibe_proxyget_model_performance_metrics — from Studio insightsLanguageModelUsageanalyse_conversation_patternscompare_model_responsesoptimise_knowledge_stacks — live Next Gen / draft / compose statussuggest_persona_improvementsrun_calibration_test, evaluate_response_qualityidentify_handoff_triggers, get_calibration_historybloom_evaluate_model, bloom_check_handoff, bloom_get_historybloom_list_behaviors, bloom_get_thresholds, bloom_validate_modellist_studio_catalogue, list_workspaces, list_personaslist_shadow_personas, list_crews, list_knowledge_stackslist_turnstiles, list_skills, list_live_contexts, list_promptslist_context_studio, list_agent_plansget_studio_entity (plural keys such as personas, plus singular aliases such as persona), get_schema_migrations, export_workflow_packdetect_nexus, list_nexus_models, query_nexus, get_insights_usageask_frontier — hand one question to the Cursor agent on this machine and return the answer in the Msty chat. Use the one-tool server (msty-frontier or python -m src.frontier_main) for a local-model chat. See Hybrid local model and Cursor agent.Phase 6 introduces behavioral evaluation powered by Anthropic's Bloom framework. Rather than testing what a model knows, Bloom tests how it behaves — detecting failure modes like sycophancy, hallucination, and overconfidence that standard benchmarks miss.
See the Bloom Knowledge Base Guide.
pytest tests/ -v
v6 ships unit tests for path resolution, read-only SQL guards, redaction, inventory/analytics, and MCP tool JSON contracts. Live smoke on Studio 2.9.2 was verified during release.
A: Run the one-tool server, put only that server in the chat's toolset, and set CURSOR_API_KEY on that server. Steps and caveats are in Hybrid local model and Cursor agent. The key stays in Msty's toolbox environment. It does not belong in this repository.
A: v5 looked for ~/Library/Application Support/Msty/msty.db. Studio 2.x stores data under MstyStudio and the Chromium File System SQLite path. v6 fixes this.
A: No. v6 targets Studio 2.9+ (works on 2.4+ layouts when the File System DB is present). Use v4.x for older process-based detection.
A: Inventory and analytics are read-only. import_tool_config refuses live writes by default because Studio may hold locks on the File System DB. Prefer Toolbox JSON import for writes.
A: Msty Nexus is the local runtime/gateway. Phase 8 detects it and lists models via its OpenAI-compatible endpoint (MSTY_NEXUS_PORT).
MIT License — See LICENSE file
Contributions welcome! Please open issues or PRs on GitHub.
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For issues, questions, or feature requests, visit: https://github.com/M-Pineapple/msty-admin-mcp
AI-powered administration for Msty Studio Desktop. 56 MCP tools for database insights, config sync, local model orchestration, and Claude handoff workflows.
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FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
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Msty Admin ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-10-28 AI-powered administration for Msty Studio Desktop. 56 MCP tools for database insights, config sync, local model orchestration, and Claude handoff workflows.