"A server offering MCP prompts as primitives for task execution" matching MCP servers:

An MCP server that helps AI coordinate sequential tool calls and maintain a comprehensive journal of execution workflows, decisions, and actions.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

Enables cluster-aware command execution and automatic task routing across distributed nodes based on system load, architecture, and OS requirements. It supports parallel execution, remote node management via SSH, and dynamic load balancing for agentic workflows.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

MCP server for managing tasks with a resource to read all tasks, a tool to add tasks, and a prompt to analyze tasks, using stdio transport.

A tutorial demonstrating how to build reusable, parameterized MCP prompt templates using FastMCP, including patterns for research, summarization, and code review.

A small, local, network-free MCP server for the RISEN prompt-engineering framework. It gives any MCP client tools to build, validate, save, and reuse structured prompts.

Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.

An enhanced MCP server that fetches prompts from GitHub repositories with intelligent discovery, composition, and management features.

Enables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.

A cross-AI-agent local task context sharing MCP server that allows clients like Codex, Claude Code, Hermes, and VS Code to read and write the same task state, enabling task tracking and context distillation.

Delegates work from MCP clients (like Claude Code) to the Codex CLI, allowing spawning of autonomous Codex subagents for tasks.

Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.

Bridges a remote, cloud-hosted agent to your local machine, exposing Pi's coding tools (read, write, edit, ls, grep, find, bash, powershell) rooted at a directory you choose. It also adds a human channel so the agent can message, question, and wait on you through tool calls instead of a platform chat UI, with OAuth 2.1 or bearer-token authorization and no persistence between runs.

Enables agents to select the provably optimal set of candidate actions under a budget, with optional conflicts and prerequisites, and to re-plan to the single best next action after each outcome. Also validates any proposed selection for feasibility.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

A task management system for LLM-based agents that stores all tasks in a single tree, available immediately after the server starts.

A comprehensive task management MCP server built with FastMCP, featuring full CRUD operations, intelligent filtering, and productivity-focused prompts.

Enables hot-reloadable prompt templates with structured reasoning frameworks, quality gates, and multi-step chain workflows that can be version-controlled and executed immediately without restarts.