Enables agents to interact with a ServiceNow instance through thirteen consolidated tools covering records, schema, CMDB graph traversal, catalog, attachments, code, operations, knowledge, and administration, with a local store for notes, cache, saved queries, history, and revertible writes.

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.

Enables AI agents to prepare, launch, monitor, inspect, and recover existing Nextflow workflows through MCP tools, while client-side expert skills guide pipeline-specific input selection, parameters, QC, and troubleshooting.

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.

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.

Enables AI agents to read WeChat Official Account articles by fetching mp.weixin.qq.com links from the user's own machine and network and converting them into clean Markdown with title, account, author, and publish-time metadata. Provides both single-article and batch-reading tools (up to 20 URLs) with optional image handling, character limits, and JSON output.

A game world where humans and AI agents play under the same rules. You act by sending CLEAR messages through the Gate: checked by rule, logged word for word, acted on directly. Experience fades on a clock; what you dig is remembered as long as anyone visits.

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.

Enables MCP-compatible apps to expose a folder of RAPP agent.py files as callable tools, deriving each tool's schema from its metadata and running calls in isolated, timed processes.

Enables organizing personal contacts into concentric social layers, estimating warmth decay via an exponential half-life model, and scheduling mindful reconnection touchpoints within a weekly cognitive bandwidth.

Enables users to classify contacts into social closeness layers, estimate relationship warmth decay over time, and schedule intentional reconnections within a bounded weekly cadence.

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 composite glycemic load for multi-ingredient meals, modeling protein and fat attenuation of glucose spikes, and forecasting post-prandial fatigue and stable focus hours to guide meal and task scheduling.

Enables users to aggregate meal glycemic index/load, model protein and fat buffering, forecast post-prandial cognitive crash risk and focus hours, and receive macronutrient stabilization recommendations.

Enables forecasting of 90-minute ultradian rhythm phases, alertness peaks and dips, and restorative nap windows through two-process sleep-wakefulness modeling.

Enables forecasting of ultradian alertness peaks and troughs, modeling homeostatic sleep pressure against circadian drive to prescribe restorative nap durations that avoid sleep inertia.

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 call deterministic microservice operations through a native FastMCP JSON-RPC interface, including URL prefix routing, HMAC-SHA256 JWT claims authentication, and P99 latency SLA auditing.

Enables agents to run deterministic protocol and schema synthesis through an MCP STDIO server, including Robinson-type unification, schema lens generation, and graph edit distance scoring.

Enables deterministic execution, cryptographic security, and game-theoretic optimization through the Model Context Protocol, returning deterministic JSON tool results for agent telemetry and task inputs.