"A to-do list for today's tasks" matching MCP servers:

Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.

A simple, beginner-friendly Model Context Protocol (MCP) server written in Python. It lets any MCP-compatible AI client (like Claude Desktop) manage a to-do list on your computer through five tools: add, view, get by ID, complete, and delete.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Provides a task passport system for handoff across AI harnesses, enabling users to list, open, create, and checkpoint tasks with stable IDs and verified state.

Enables agents to query and append shared memory in a local, user-owned Markdown/Obsidian vault through hybrid vector and keyword retrieval with reranking, while redacting secrets and PII into sanitized, minimum-viable briefs. It also dispatches approved tasks to Wajo Fo's MCP endpoint over StreamableHTTP or SSE and writes execution receipts back to the vault.

A robust MCP server that transforms OneNote notebooks into an AI-accessible knowledge base for Gemini Spark, enabling natural language queries to list, read, and search notes via Microsoft Graph API.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

Provides AI agents with a local, private Markdown-based memory vault and SQLite search. Enables agents to search, read, list, and traverse linked knowledge pages via MCP with zero external runtime dependencies.

Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

A plain-files brain template and MCP server that lets models read owned, portable working memory via list, read, and grep-style search tools.

Self-hosted AI companion whose MCP server lets Claude, Cursor and other clients search her long-term memory, document library and notes, read today's plan and to-dos, and ask her questions. Read-only by default; write tools follow her approval settings.

Simple, fast, long-term memory for your AI chatbots, agents, and MCP tools. Give your LLM a persistent memory using a local SQLite file. No complex database servers, no heavy cloud setup, and zero C++ compilation errors. Works everywhere.

Standalone MCP server for Obsidian vaults - hybrid search (FTS5 + vector + cross-encoder reranking), images and PDFs in agent-readable form, Kanban-aware tasks (Tasks-plugin + Dataview formats), structured memory with topic recall, fine-grained read/write tools for optimal token efficiency, and link graph support. Run locally, self-host, or one-click deploy for remote access. OAuth 2.1.

Free Industry 4.0 / IIoT tools, no API key or account: lint MQTT Sparkplug B topics, check a Unified Namespace (UNS) for naming and hierarchy problems, and run an industrial AI-readiness diagnostic for manufacturing digital transformation and smart-factory projects. Works in Claude Code, Codex and any MCP client.

Provides an AI agent with a searchable markdown notes vault, offering tools to create, read, list, search, update, and delete notes stored as plain .md files.

A Model Context Protocol server that connects MCP-compatible clients like Claude and VS Code to your Readwise Reader library, allowing them to list, retrieve, and update documents in your personal knowledge repository.

An MCP server that enables LLMs to pull-based search through Clawket's RAG repository for exploratory and conditional queries. It provides read-only access to search artifacts, tasks, and decisions via HTTP API.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

MCP server that lets agents create and update persistent concept maps via the NodeLand API, returning shareable URLs for humans to view, embed, and keep editing.

An MCP server that records decisions, rejected alternatives, and justifications, and retrieves them later to avoid re-litigating past choices. It stores data locally in SQLite and Markdown.

A production-oriented Agent Operating System kernel that provides multi-graph memory, durable tasks, portable skills, attestation, and plan-based monetization for MCP-based agents.

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

An MCP server that reads a team's interviews, tickets, and docs to build a model of the product, exposing tools to ask questions, list contradictions and gaps, and draft documents, with all answers citing their source fragments.

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.