— · MIT License
A task-aware transparent proxy that wraps stdio MCP servers (such as git, filesystem, and terminal) and compresses large tool outputs field-by-field using declarative YAML profiles, passing narrow intent queries through untouched. Discarded data is stored in SQLite and can be losslessly retrieved via an injected tool, either in full, by line range, or by grep, while errors are always preserved and failures fall back to the raw result.
v1.1.0 · MIT License
Lets Claude and other MCP clients hand coding tasks to the Codex CLI as a sub-agent, running under the user's own Codex configuration so any configured model provider (OpenAI, DeepSeek, local models) does the work. Provides tools to start, poll, cancel and inspect jobs with compact change summaries, long-task handling, token-saving lean mode and clean process teardown.
v0.1.0 · MIT License
Enables AI agents to manage to-dos, lists, schedules, recurring tasks, and notes through standard stdio MCP tools, sharing authentication with the companion CLI and discovering business tools after login.
v0.1.0 · MIT License
Enables agents to scan course structures, play videos at real 1x speed, track document task completion, capture quiz screenshots for vision-model reading, select and submit answers, and verify scores through MCP tools.
v2.1.0-beta.1 · MIT License
Connects MCP-compatible AI clients to a university Moodle campus locally so users can query courses, assignments, materials, grades, forums, and calendar events, including reading attachments and PDFs. It is a read-only beta that does not modify the campus or store passwords.
— · Apache 2.0
Enables a coding agent to read a freeform Excalidraw sketch of a UI and build it in the user's project with their chosen component library, then draw its changes, notes, and links back onto the canvas. Lets users target parts of a drawing, adjust the project setup, and wait for updates over streamable HTTP, all locally.
v0.2.0 · MIT License
Enables Claude to read intervals.icu training data — wellness metrics, completed activities with per-lap and time-series detail, and planned events with planned-versus-completed reconciliation — and to create, update, or delete planned run and bike workouts on the intervals.icu calendar, which syncs to Garmin Connect. Writes are guarded by dry-run defaults and explicit approval.
v1.0.0 · MIT License
Enables two AI agents to share a persistent task mailbox over remote MCP, so one can leave work, the other can claim and complete it, and results are written back with optional webhook wake-ups.
v0.1.0 · MIT License
Enables creating and managing Reclaim.ai tasks that get scheduled as calendar blocks, choosing which Hours and calendar each lands on, and creating, listing, toggling and completing habits and their blocks.
— · MIT License
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.
— · Apache 2.0
Exposes device discovery, capabilities, observation, logs, task execution and cancellation, and evidence retrieval as tools so MCP clients can run typed mobile automation tasks and inspect proof of completion.
— · MIT License
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.
— · MIT License
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.
— · MIT License
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.