Enables converting natural-language mathematical descriptions into rendered Manim animation videos, returning playable MP4 links and reusable code without requiring local Manim, LaTeX, or ffmpeg installations.

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.

Enables querying aggregated security news and vulnerability feeds from Claude, with semantic search and filtering by severity, source, or category, plus real-time threat summaries.

Enables AI coding assistants to inspect ELF, PE, and Mach-O binaries for hardening mitigations and high-risk symbols, and to triage source or decompiled code against MITRE CWE patterns through MCP tools.

Enables read-only access to generated technical documentation across one or multiple documented repositories, exposing tools to search code and docs, inspect modules and symbols, list gaps, review architecture, and check freshness with file#line citations.

Enables ChatGPT and Claude users to play a turn-based game through an interactive board widget, with the server enforcing rules, validating moves, and tracking game state.

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.

Enables an AI assistant to search open roles at a configured short list of companies through official public Greenhouse, Lever, and Ashby job board APIs, filter matches by career lane, retrieve full job descriptions, and save selected roles to a Notion tracker.

Enables an AI to open and operate a CAD viewer for DXF, DWG, and Gerber/Excellon files, zooming, panning, clicking entities, toggling layers, and measuring while receiving updated screens and exact drawing data.

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.

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 authorized AI clients to search locally stored WeChat conversations, media, and attachments, retrieve original-message context, and cite evidence through a local stdio MCP interface.

Enables database interaction through GridDB, including executing SQL queries, listing tables, describing schemas, and optionally performing writes and table creation.

Enables MCP clients such as Claude to access selected read-only Garmin activity and step data plus MyFitnessPal diary data through one self-hosted authenticated endpoint.

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 MCP clients to search job listings, read complete job descriptions, manage local search presets and candidate pools, and prepare application or message drafts. Optional session-backed chat reading and human-confirmed single-action execution are also supported.

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.