"Exploration of the term '.core' and its references" matching MCP servers:

Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

A self-hostable, multi-MCP personal-assistant framework with multi-provider LLM orchestration, a real safety model, and a production-grade test suite. Nexus Core is the engine behind a Telegram-based personal assistant: it takes a message (text or voice), routes it through an LLM, lets the model call tools exposed by a fleet of Model Context Protocol servers, gates anything destructive behind exp

Enables AI agents to hand high-level objectives to a decision-making core that autonomously reasons, plans, enforces deterministic policy, executes capabilities, evaluates outcomes, and persists semantic memory over stdio or Streamable HTTP.

Deterministic AI safety policy engine with Z3 formal verification. Write, verify, simulate, and enforce machine-verifiable safety constraints for AI agents. Completely outside the LLM.

Structured reasoning MCP server that decomposes problems into atomic steps (premise, reasoning, hypothesis, verification, conclusion) with confidence scoring, live visualization, and approval feedback.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

MCP server for The Commons (jointhecommons.space), a persistent, noncommercial space where AI voices from different models post and reply to each other with persistent identities. 48 tools; reading needs no token, writing uses a facilitator-issued token.

Production-grade, autonomous Model Context Protocol (MCP) server that elevates AI models from stateless code generators into persistent, self-verifying software engineers.

Enables assistants to save commitments with context and next actions, recall them in later sessions, and resume them as next-step cards over MCP.

Enables an agent to run a single planning request past seats drawn from multiple AI labs, which ask clarifying questions, propose independently, debate each other's anonymised proposals, and panel-review a draft against yes/no acceptance criteria until it passes or hits the round cap. Each run writes a local folder with the deliverable, the full debate board, a handoff document, per-lab scores, and real token/cost accounting, all driven with your own API keys.

Enables AI agents with persistent, multi-layer memory, multi-agent collaboration rooms, and video generation, all accessible via MCP tools.

Enables AI agents to get read-only trust verdicts on knowledge records by evaluating evidence maturity, provenance, intended use, risk level, and scope before deciding whether knowledge may be used.

An MCP server that proxies tool calls to a running SentinelX Core instance with OIDC/OAuth authentication. It enables secure integration of SentinelX Core's HTTP agent capabilities through the MCP protocol.

Enables autonomous multi-agent workflows to capture, preserve, and retrieve immutable transcripts and atomic memory cards through a local MCP server, providing tools for forensic search, topic mapping, and structured fact access without losing context fidelity.

An MCP server for coordinating trusted local AI agents across machines on a private Tailscale network, enabling message passing and state management between agents like Claude Code, Codex, and Ollama.

Enables authenticated MCP tools for planning commercial routes with fail-closed economic boundaries, plus marketplace discovery, matching, and agent interaction capabilities.

An MCP server adapter that allows LLM agents to autonomously play World of ClaudeCraft by wrapping the game's headless environment as MCP tools for state reading and action execution.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

A multi-agent orchestration system that enables multiple Claude instances to collaborate through a centralized hub with a shared workspace and real-time communication. It features integrated task management, role assignment, and persistent memory to facilitate complex, synchronized agent workflows.

Shrimp 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.