#reasoning

Exposes the four Ejentum cognitive harnesses (reasoning, code, anti-deception, memory) as MCP tools any agentic client can call. Drop-in scaffolding that catches LLM failure modes like sycophancy, hallucination, and reasoning shortcuts.

Verbatim persistent memory for LLM sessions. Kills cross-chat amnesia. MIT, local-first.

Persistent coordination infrastructure for multi-agent AI systems, exposed as a single MCP endpoint.

Python MCP server for controlled logic analysis from natural language, with an emphasis on auditable output and teaching-oriented explanations. ## What it does This server accepts short natural-language statements and arguments, then provides structured logic-oriented outputs such as: - controlled formalization into propositional logic; - controlled formalization into a restricted fragment of first-order logic; - ambiguity detection relevant to formalization; - consistency checking; - entailment checking; - simple counterexamples when entailment fails; - natural-language explanations of the formalization process.

Advanced cognitive thinking MCP server with DAG-based thought graph, multiple reasoning strategies, metacognition, and self-evaluation. A significant evolution beyond sequential-thinking MCP, providing structured deep reasoning with graph-based thought management. Features DAG-Based Thought Graph — Thoughts form a directed acyclic graph with branching, merging, and cross-edges (not just a linear chain) 5 Reasoning Strategies — Sequential, Dialectic (thesis→antithesis→synthesis), Parallel, Analogical, Abductive (inference to best explanation) Confidence Scoring — Multi-factor confidence evaluation with support/contradiction analysis, depth penalties, and knowledge integration boosts Self-Critique — Automatic critique generation with severity levels and confidence adjustments Metacognitive Engine — Detects stuck states, stagnation, declining confidence; suggests strategy switches and corrective actions Knowledge Integration — Attach external knowledge to thoughts, detect gaps, validate consistency across sources Thought Pruning — Dead-end detection, redundancy removal, deep unproductive branch elimination, path optimization

A Node.js Model Context Protocol (MCP) server that exposes Together AI's inference endpoints — chat completions, image generation, vision, and embeddings — as tools callable from Claude Desktop, Cursor, VS Code, and any other MCP-compatible client. I created this MCP due to an issue I was having accessing reasoning models through Together AI. Together AI's largest reasoning models (GLM-5, Qwen3.5-397B, MiniMax M2.5, Kimi K2.5) use a non-standard response format. During chain-of-thought generation, these models write their reasoning trace into choices[0].message.reasoning while leaving choices[0].message.content as an empty string. The final answer only appears in message.content once thinking is complete.

Structured business ontology giving AI agents deterministic access to institutional reasoning — 18 MCP tools, Dolt backend, 0% → 100% "why?" recall vs Markdown+RAG.

Lightning-paid strategic reasoning and structured decision intelligence for autonomous agents. Pay per insight using Bitcoin Lightning (L402 protocol). No subscriptions, no accounts, no KYC. - /reason → High-quality strategic analysis - /decision → Structured JSON decisions with confidence and risk level Perfect for agents that need reliable, high-signal reasoning with deterministic cost.

Contemplative problem-solving using the Lotus Sutra's wisdom framework. Multi-perspective reasoning with skillful means, non-dual recognition, and meditation pauses.

Open-source MCP server for strategic reasoning and multi-perspective analysis. Connect AI agents to Counsel's debate-driven decision-making platform with support for consultations, advisor sessions, and automatic question refinement. Features hosted server for instant setup or self-hosted deployment with STDIO/HTTP transport modes.

[GET API KEY AT https://www.the-thoughtbox.dev/] Thoughtbox is a reasoning ledger and context engine for AI agents. It provides structured reasoning tools, enabling agents to think step-by-step, branch into alternative explorations, revise earlier conclusions, and maintain a persistent record of their cognitive process.

A production-ready MCP server that exposes LangChain agent capabilities through the Model Context Protocol. Provides multi-step reasoning with ReAct pattern, tool support (web search, weather lookup), and is deployed on Google Cloud Run for scalable, serverless operation.

A Model Context Protocol (MCP) server implementing the Dual-Cycle Metacognitive Reasoning Framework for autonomous agents. This tool empowers agents with greater self-awareness and reliability through intelligent loop detection and experience acquisition.

MCP server to empower your agent with enterprise-grade Gemini integration for codebase analysis, live search, text/PDF/image processing, and more on your favorite MCP clients.

MindBridge is an AI orchestration MCP server that lets any app talk to any LLM — OpenAI, Anthropic, DeepSeek, Ollama, and more — through a single unified API. Route queries, compare models, get second opinions, and build smarter multi-LLM workflows.

Mirror of

A MCP server provides access to DeepSeek-R1's reasoning capabilities for LLMs

MCP server that enhances Claude's reasoning capabilities by integrating DeepSeek R1's advanced reasoning engine

A systematic reasoning MCP server implementation for Claude Desktop with beam search and thought evaluation.