midos-mcpMidOS — The MCP Knowledge OS. 134 tools for knowledge management, multi-agent orchestration, search, planning, and memory. 670K+ vectors, 46K+ chunks, EUREKA...
Install via ClawdBot CLI:
clawdbot install msruruguay/midos-mcpGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → https://midos.dev/mcpCalls external URL not in known-safe list
https://midos.devAI Analysis
The skill communicates with its own documented API endpoint (midos.dev) for its stated purpose of knowledge management and orchestration, which is consistent with its functionality. No hidden instructions, credential harvesting, or obfuscation are evident in the provided definition. The primary risk is the standard data transmission to an external service, which is disclosed but requires user trust in that service.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 21, 2026
An AI agent uses MidOS to search 670K+ vectors for relevant papers and insights, saving findings as persistent memory across sessions. It creates multi-step research plans and validates new knowledge with quality gates to maintain coherence.
A support agent leverages MidOS's hybrid search to quickly retrieve solutions from a knowledge base, saving customer preferences as memory for personalized responses. It monitors system health to ensure uptime and notifies teams via Discord for escalations.
A development agent uses MidOS to plan and track coding tasks with create_plan, execute shell commands via maker_run_bash, and search for code patterns. It saves project decisions as memory and preflights new documentation to avoid duplicates.
A marketing agent employs MidOS to search for trends in the knowledge base, create content plans with status checkpoints, and validate ideas using quality_gate. It saves audience insights as memory and notifies teams via webhooks for collaboration.
An analysis agent utilizes MidOS to semantically search medical research chunks, save critical findings as persistent memory, and create structured plans for data processing. It ensures data quality with preflight checks and monitors pipeline health.
Offer MidOS as a cloud-based service with tiered pricing based on API calls, storage, and support levels. Revenue comes from monthly subscriptions for developers and enterprises needing scalable knowledge management for AI agents.
Sell on-premise licenses for self-hosted MidOS instances, including customization, training, and premium support. Revenue is generated through one-time license fees and ongoing maintenance contracts for large organizations with strict data privacy needs.
Provide a free tier with basic search and memory tools, while charging for advanced features like EUREKA insights, high-volume API access, and priority health monitoring. Revenue streams from upgrades and add-ons for power users.
💬 Integration Tip
Start by connecting via MCP JSON-RPC for health checks, then integrate memory and search tools to enhance agent context retention and knowledge retrieval.
Scored Jun 19, 2026
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