A zero-dependency MCP suite exposing computational tools across metabolic, cardio-renal, chronobiology, neuro-recovery, and biomechanics domains. It enables clients to derive longevity and physiology metrics such as autophagy index, glucose-ketone ratio, glycemic variability, peripheral resistance, nocturnal BP dipping, DLMO clock time, melanopic lux, caffeine clearance, EEG fatigue entropy, and grip vitality age from user-supplied measurements.

Exposes MCP tools that compute longevity and metabolic metrics (autophagy index, GKI, MAGE), cardio-renal biomarkers (BUN/creatinine ratio, cardiac output and TPR, nocturnal BP dipping), chronobiology estimates (DLMO, melanopic lux, caffeine clearance), plus neuro-recovery and biomechanics scores. Runs as a zero-dependency Python JSON-RPC 2.0 stdio server so any MCP-compatible client can query these physiological domain calculators.

Enables AI agents to browse and manage a gThumb image library by reading and writing catalogs, tags, ratings, comments, thumbnails, and search results directly in gThumb’s own data.

Gives AI agents read-only access to curated, deduplicated, and well-described data products, complete with source metadata, freshness tracking, and per-agent permissions that preserve the source's access rights. The server can also answer "I don't know" rather than guessing when the approved data doesn't cover a question.

Enables AI agents to remember people, projects, places, and topics across conversations under a strict token budget, returning compact handles with expandable details while preserving changes, provenance, and encrypted self-hosted storage.

Enables AI agents to query Huawei Cloud catalog and list prices, build quotes, and generate share links on the Huawei Cloud pricing calculator.

Enables AI agents to store decisions as a versioned history, linking each new decision to the one it replaces so that recall always resolves to the decision currently in force instead of obsolete ones. It runs fully locally on a single SQLite file with BM25 search, and can optionally detect replacements automatically via an LLM or heuristic linker.

Enables agents to run SweetScape 010 Editor Binary Templates and Scripts headlessly against local files. It provides tools to locate the editor binary, execute templates or scripts, and use controlled exit behavior for compile and runtime failures.

Enables AI agents to query and trade through Interactive Brokers using 38 tools for order placement and management with risk checks, account and position data, market and historical data, and options analytics. Includes diagnostics and configurable safety limits, designed primarily for paper trading.

Causal memory layer for AI agents — MCP server that records decision→outcome relationships. Survives compaction.

Supercharge your AI agents by versioning, tracking, and merging overlapping skills.

Enables AI agents to list and compare LLM API prices per million tokens, rank the cheapest models by context and keyword, look up GPU rental rates per hour by provider, and estimate self-hosting cost per million tokens against API pricing. Pricing data comes from OpenRouter's public models endpoint plus a dated GPU price CSV, with source URLs and explicit notes when data is missing.

Enables AI agents and MCP clients to run on-demand OSINT harvests for public emails, subdomains, hostnames, IPs, and LinkedIn profiles, returning structured JSON and allowing prior results to be retrieved by harvest ID.

Enables AI agents to search and browse a local, CJK-aware full-text index over coding-agent session histories (Claude Code, ZCode, Kimi, dsh, Qoder, OpenCode) via tools for searching sessions, listing sessions, fetching original messages, listing agents and tools, and refreshing the index.

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 AI agents to connect to security cameras, detect objects with YOLOv8, recognize known faces, monitor restricted intrusion zones, capture annotated snapshots, and query a persistent SQLite event history.

Enables any MCP-compatible client to persist long-term memories for AI agents, with LLM-based fact extraction, semantic vector search, update/delete/list operations, and queue status checks across sessions.

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.

Enables external AI agents and CLI tools to control DaVinci Resolve Free and Studio through a local file-polling Lua bridge, exposing project, timeline, media, marker, and render operations as typed MCP tools.

Enables AI agents to test WCF/SOAP and REST services directly, with WSDL discovery, authenticated calls, and deterministic assertions. Supports YAML multi-step scenarios with variable extraction, JSONPath/JSON Schema checks, and CI runs without spawning PowerShell or curl.

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.

Enables AI coding agents to automatically compress context at agent-judged task boundaries, write incremental structured session snapshots, and maintain per-fact long-term memory for priority restoration across sessions.

Enables AI agents to query a Python codebase as a knowledge graph over MCP, exposing symbol search plus callers, callees, and module dependency tools.

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.