10 skills found
mindsdb / mindsdbQuery Engine for AI Analytics: Build self-reasoning agents across all your live data
cjo4m06 / mcp-shrimp-task-managerShrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.
PV-Bhat / vibe-check-mcp-serverVibe Check is a tool that provides mentor-like feedback to AI Agents, preventing tunnel-vision, over-engineering and reasoning lock-in for complex and long-horizon agent workflows. KISS your over-eager AI Agents goodbye! Effective for: Coding, Ambiguous Tasks, High-Risk tasks
AVIDS2 / memorixLocal-first memory platform for AI coding agents. Git memory, reasoning memory, and cross-agent recall via MCP.
fabio-rovai / open-ontologiesAI-native ontology engine: a Rust MCP server with tools for building, validating, querying, and reasoning over RDF/OWL ontologies. In-memory Oxigraph triple store, native OWL2-DL tableaux reasoner, SHACL validation, SPARQL, versioning. Single binary, no JVM.
cyqlelabs / mcp-dual-cycle-reasonerA MCP server implementing the Dual-Cycle Metacognitive Reasoning Framework for autonomous agents. A loop prevention and experience recall mechanism.
angrysky56 / emotion_aiThe Aura Emotion AI system has chroma with a local embedding model, memvid qr code mp4 infinite memory, brainwave and neurochemical simulations, sociobiological reasoning, autonomous subsystem processing with a Gemini flash model so the main model is less taxed, is a MCP client with adaptive tool learning and MCP server.
hanw39 / ReasoningBank-MCPImplementation based on the paper "ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory"
agentralabs / agentic-memoryPersistent cognitive graph memory for AI agents — facts, decisions, reasoning chains, corrections. 16 query types, sub-millisecond. Rust core + Python SDK + MCP server.
tanaikech / nexus-mcp-extensionNexus-MCP solves Tool Space Interference in LLMs. It uses a single gateway to aggregate multiple MCP servers and employs a deterministic 4-phase workflow (Discovery, Mapping, Schema Verification, Bridged Execution) to prevent context saturation and tool hallucinations, maintaining reasoning accuracy with massive tool ecosystems.
