Enables AI agents to drive a real Chromium browser by receiving compact, token-efficient page maps and only the changes after each action. It guards against hidden prompt injections, blocks payments, sends and deletions until the user approves, and lets agents learn site-specific notes over time.

Enables agents to bring claims, situations, and Scripture passages to five doors (Check, Find, Walk, Word, Keep) and receive a verdict, the worked reasoning trail, cited sources, and a re-checkable content-addressed seal. It covers 77 verifier domains and 880k+ cards fully offline, so answers are found, verified, and sealed rather than generated.

Exposes the full Plexim PLECS Standalone JSON-RPC interface as MCP tools, letting agents auto-start and connect to PLECS to load and edit models, run simulations and analyses, manipulate scopes and webserver data, and perform code generation or FMU export with structured, size-aware results. Includes write guardrails, concurrency handling for long simulations, and batch/raw passthrough escape hatches.

Trusty Squire gives coding agents the ability to provision, ship, and pay — without your keys or card ever leaving the vault.

Enables stateless, pure-visual control of Android devices and emulators through adb shell, providing screen capture, coordinate-based taps, swipes, keyboard input, and arbitrary adb command execution for agent-driven interaction.

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

Enables learners to browse, read, and be quizzed on saved lessons inside Claude Desktop and Claude Code, and enables five Claude agents to build fact-checked K–College lessons through guarded, pinned MCP tools.

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.

Exposes four read-only tools over extracted Hacker News "Who is hiring?" job posts — postings_search, posting_get, skills_top, and skills_trend — so an MCP client or agent can search postings, look up individual posts, rank top skills, or chart skill trends over time. Tools return only structured extracted fields and HN links (never raw post text) from a read-only SQLite database, including salary sorting and a hard row limit to keep queries cheap.

Enables agents to observe a desktop and perform mouse and keyboard actions through ESP32-based BLE or USB HID hardware, with local action translation and no second model in the MCP path.

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.

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.

Connects MCP hosts and LangChain agents to a local WAHA (WhatsApp HTTP API) instance, exposing tools for session management, chats, messages, contacts, and sending text, images, or files. It also provides an operational skill prompt covering lifecycle, chat ID formats, send guardrails, media rules, and error handling.

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 agents to guard external API calls with circuit-breaker health checks, success/failure reporting, and recovery state inspection, including exponential backoff with jitter and fail-fast rejection.

Enables AI agents to monitor live token consumption and rate-limit windows across providers and assess whether expensive actions are justified before exhausting quotas, with optional budget guardrails.

Enables AI agents to drive remote desktops through the local RustDesk client on macOS, launching sessions, capturing the session window, and injecting keyboard and mouse input. Exposes session lifecycle, screenshot, input, and device book capabilities as MCP tools.

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.

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Governance standard and reference toolset for LLM-maintained knowledge corpora