Enables AI agents to read the local, already-logged-in WeChat account's chat history: fetch recent messages per contact for reply suggestions, bulk-export all conversations into a local SQLite index for full-text and semantic search, and export media or Moments timelines as offline HTML. Everything runs locally and read-only on macOS, exposing 15 MCP tools plus a matching CLI.

Enables LLM clients to explore and query a local SQLite database through read-only, typed tools for table listing, schema inspection, ad-hoc SQL, customer lookup, and sales summaries.

Enables AI agents to operate a self-hosted double-entry personal finance ledger: answering spending, net-worth and cash-flow forecast questions, searching transactions, and managing schedules, rules and imports through audited, reversible tools. Read and write access is scoped by token, with privacy controls over what financial details reach the agent.

A read-only MCP server that lets AI agents query a user's own Garmin Connect data via Garmin's official Personal API. It exposes activities, daily wellness metrics, sleep and recovery, and body/profile data as tools for natural-language analysis.

Gives AI agents a durable, locally hosted temporal memory built from a markdown vault you own, exposing hybrid semantic/lexical/entity search over events, threads, transcripts, entity relationships with validity dates, and patterns with confidence decay. Writes are approval-gated, so agents can draft, commit, and sync new memories while keeping every index rebuildable and nothing leaving your machine.

Exposes tools that let an agent read a CV, search the Arbeitnow job board for Berlin AI/ML working student roles, score each vacancy against the CV, draft cover letters whose every claim cites CV facts, and queue them for human approval. The same tools can be driven from other MCP clients such as Claude Desktop, with scoring done deterministically in code and limits enforced outside the prompt.

Enables AI coding agents to manage agile boards and notes, including cards, epics, sprints, labels, progress and verification records tied to commits, human-reviewed criteria and decisions, and Area documentation.

A read-only MCP server that gives AI agents access to a user's Last.fm listening history, including recent plays, top tracks, artists and albums, loved tracks, tags, and similar-track/artist data. This lets the agent inspect someone's taste and discover music they haven't heard before, which it can then play through its own music tool.

Enables unattended Claude agents to send Discord notifications and ask humans questions, receiving answers via buttons, selection menus, or thread replies, with pending answers recoverable on later runs.

Exposes agent-facing tools that let a personal AI agent submit each proposed action for an allow, require_approval, or deny verdict against OWASP PAA10 policy rules, plus tools to record provenance-tagged memories, log refusals, read status, and trigger a self-stop. Its decisions are advisory unless paired with the project's gating proxy or hook, which enforce them.

Enables MCP clients to manage Knowledge Agents and Jams, including creating and querying agents, uploading and inspecting documents, launching agent discussions, and retrieving responses and results.

Connects AI agents to a creative platform's canvas, image, video, audio, subject, and storyboard capabilities, enabling natural-language parameter lookup, job submission and tracking, credit-controlled execution, and asset retrieval.

Enables LangChain ReAct and deep agents to manage WhatsApp sessions, chats, contacts, and messages—including sending text, images, and files—through MCP tools backed by a local WAHA instance.

This MCP server enables users to analyze personal reading and media streams by computing Shannon entropy, detecting Jaccard redundancy and echo chambers, and ranking content sources by decibel SNR to produce pruning recommendations and high-signal curation.

Enables users to audit personal reading streams by quantifying category diversity with Shannon entropy, detecting lexical redundancy and echo chambers via Jaccard similarity, and ranking content sources by decibel signal-to-noise ratio for pruning recommendations.

Enables computing physiologically adaptive focus durations and personalized micro-break prescriptions by modeling exponential mental fatigue and Yerkes-Dodson arousal for sustainable work-rest cycles.

Enables agents to use ACT-R spreading activation memory, semantic association graphs, and automated memory consolidation via the Model Context Protocol.

Enables agents and applications to detect, inspect, and neutralize prompt injection, jailbreak attempts, and hidden instruction escapes in untrusted text before it is passed into prompts.

A read-only MCP server that lets AI assistants search and browse the Coolapk community — posts, comments, topics, user profiles, home feeds, and images — with built-in login reuse, rate limiting, and risk-control fallbacks. All access is strictly read-only, so agents can look up community information without any write operations.

Enables AI agents to search and invoke 1,939 Atlassian automation tools across Jira, Confluence, Bitbucket, Admin, Assets, and more, with cached reads and JSON-RPC over stdio. It helps agents find tools without calling Atlassian and execute operations while reducing rate-limit pressure.

Enables an AI agent to list the 1 € Crous & Go student menus, ask which variant you want, and place and pay for the order through your own Izly account, with dry runs, a kill switch, a 1 € price cap, and explicit confirmation before any real purchase.

This server provides a standardized interface for interacting with the NovelAI image generation API, enabling agents to build and execute complex image creation workflows. It supports various generation types, from text-to-image and inpainting to parameter configuration, while providing Anlas cost estimation and semantic tag search.

Exposes three read-only tools that list local Agent and MCP runtime candidates, inspect running processes, and check a live runtime against an approved artifact expectation. Returns explicit verdicts such as matched, stale, leaked, conflict, unknown, or not running without exposing argv, environment values, or file contents.

Enables coding agents to perform semantic Python AST diffing across git boundaries, detect breaking changes, and generate concise PR triage summaries for reviewers via the Model Context Protocol.