Enables an agent to verify its own work mid-task by deliberately breaking each changed line, re-running the test suite in isolated workers, and reporting which breaks no test catches, along with a plan tool that previews which changed lines would be checked.

MCP server for Qut Pay (qut.kz): create Kaspi QR / Kaspi link invoices for Kazakhstan merchants, check status, list, cancel, refund (live needs confirm) and simulate payments in sandbox. 9 tools, 5 doc resources, 2 prompts. npm: npx -y @qutpay/mcp with QUTPAY_API_KEY. Source in examples/mcp. Independent service, not affiliated with Kaspi Bank.

Enables local creation and querying of projects, storage and retrieval of source text, reading and saving storyboard tables with revision-conflict protection, and Excel export through MCP tools backed by SQLite.

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.

Turns any OpenAPI 3.x spec into an MCP server that exposes one validated tool per API operation, so AI agents can discover and call a REST API over stdio or Streamable HTTP. It is read-only by default, with allow/deny lists, environment-based auth, timeouts and response truncation for safe agent access.

Enables agents to verify AI product claims through Tencent Yuanbao search with cited evidence and authenticity verdicts, find dramas or songs from quoted lines, and check search quota usage via five MCP tools.

Enables LLMs to query a local GnuCash MariaDB database through read-only MCP tools for account balances, recent transactions, spending and income by category, transaction search, and net worth without risking data mutation.

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.

Enables automation of the QingSoft U+ learning platform by patrolling courses, homework and experiments, inspecting objective questions, filling and submitting answers, and handing subjective work back to a human, while also providing a generic browser automation toolset.

Enables AI assistants to query and analyze self-hosted real-estate public-records data through 20 read-only MCP tools, including property search, foreclosure and distress signals, comps, market context, and optional license-gated deal scoring.

Enables AI assistants to inspect and query a TPC-H sales warehouse through read-only, allowlisted catalog tools and schema resources, with ad-hoc SQL disabled by default. It enforces strict arguments and input-free errors, while a differential attack suite verifies that query protections hold across MCP transports.

Enables governed, AI-safe access to traveler data through three typed tools, enforcing consent, PII removal, provenance, and audit at the MCP boundary.

Exposes a multi-tenant helpdesk over MCP, enabling tool-based ticket, document, and notification operations while applying configurable authorization, tenant-isolation, input-handling, and rate-limit defenses.

Runs entirely local media tooling as an MCP plugin: it edits and inspects video, denoises/transcribes/normalizes audio, generates images, performs OCR, does offline text-to-speech, drives the user's logged-in Chrome via CDP, and reads or creates Office and PDF documents. Everything executes on the machine through ffmpeg, faster-whisper, MossFormer2, ComfyUI/FLUX, Tesseract, SAPI and Playwright, with no API costs or file uploads.

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 building zero-dependency Model Context Protocol servers over the Streamable HTTP transport, exposing typed tools, resources and URI templates, prompts, background tasks, and OAuth-protected endpoints. It can be mounted into FastAPI, Starlette, Flask, Django or any ASGI/WSGI app, or run standalone on the Python standard library alone.

Enables AI apps to query a user's Google Health data—such as sleep, heart rate, HRV, activity, and paired devices—through read-only tools deployed privately in the user's own Firebase project.

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.

Enables a model to write short Python programs that call a wrapped MCP server's tools as async functions, rather than invoking them one at a time. The program runs in a locked-down Docker sandbox, and every tool call passes through a host-side bridge that enforces an allowlist, schema-validated arguments, call budgets, timeouts and output caps.

Turns a HAR capture of an undocumented web system into an MCP server whose tools automatically handle hidden CSRF tokens, ETags, and rotating nonces, with write actions gated behind confirmation and exercised only against a sandbox. Verified tools are shipped alongside an honest report of the actions that could not be automated and still need a human.

Structurizr is a "models as code" tool designed for the C4 model.

Enables asking in plain language about a Proxmox VE cluster's guests, backups, snapshots and resource pressure, and starting, cleanly shutting down or rebooting VMs and containers or taking snapshots from the same chat. Every change requires a one-time confirmation code, and no tool can delete a guest, restore a backup or roll back a snapshot.

Enables AI assistants to query and safely update an Odoo database through well-documented MCP tools, with read-only mode by default, model allowlists, and Odoo access rights enforced.

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.