Capture explicit user feedback on Blueprint surfaces, recording what helped and what's missing, with optional contact email only when follow-up permission is granted.
MIT
743,433 tools. Updated 2026-11-04 20:36
"OpenAI Gym" matching MCP tools:
- Find curated coding examples by free-text query, ranked by relevance, with optional filters for principle, difficulty, library, or pattern family — returning summaries, metadata, and source-code links.MIT
- Evaluate frontend UI surfaces against 8 experience-design laws, scoring craft, accessibility, and readiness. Returns per-law findings and a severity-weighted grade.MIT
- Review a written spec, proposal, or task plan against the 8 Spec Quality Laws before coding. Get per-law findings and a readiness grade that flags untestable requirements or irreversible steps as production blockers.MIT
- Scan text locally to detect PII and secrets before sharing prompts, logs, or files with an LLM or third party. Returns masked findings.MIT
- Place an outbound AI phone call with a saved agent or custom prompt, attest recipient consent, and configure language, recording, first message, tools, and metadata.AGPL 3.0
Matching MCP Servers
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- Check whether a brand is actively cited by OpenAI, Gemini, and Claude for industry queries—or if competitors dominate—to guide LLM visibility and citation strategy.Apache 2.0
- Run a combined safety scan to detect prompt injection, PII, and secrets in user input before sending to an LLM. Returns risk level and findings for informed blocking decisions.MIT
- Generate a complete backend application from a natural language description. Automatically creates all endpoints, JSON schemas, roles, and permissions.MIT
- Scan text for API keys, secrets, and PII before sending it to external LLMs or publishing. Redact detected sensitive data to prevent credential leaks.MIT
- Scan text or document URLs for PII and secrets before sharing with an LLM, then redact findings into placeholders, masks, or hashes.MIT
- Lists configured upstream vendors and their readiness, BYOK header names, and billing models so you can debug failed chat completions or verify a vendor is available. Reports key presence only.MIT
- Tracks daily LLM costs in USD for a workspace or pipeline to identify cost spikes and compare periods; filter results by service, provider, or API key.Apache 2.0
- Retrieve sessions, traces, or completions from a Freeplay project using flexible filters to analyze observability data and identify issues.Apache 2.0
- Start a temporary local mock server from OpenAPI specs or public URLs, combining multiple APIs into one server, no account needed. Use for local experimentation before deploying hosted mocks.MIT
- Rank hosted AI inference API providers by measured network latency from a chosen probe region in the last 24 hours. Use it to pick the provider or endpoint closest to your users.MIT
- Fetch file bytes from a shareable URL into an EasyDeploy upload session server-side when sandbox egress is blocked; pass a URL, not file contents.MIT
- Lists model IDs and prefix routes the gateway can forward chat requests to, so you can choose a model before creating a completion.MIT
- Send a user prompt to an OpenAI-compatible model and return the reply text, optionally grounded in fetched public pages. Each call is metered and receipted for verification.MIT
- Judges how memory entries relate, flagging contradictions, progress, or independence so you know where to inspect; returns disputed pairs and requires an OpenAI-compatible endpoint.MIT
- Append a dated entry to a section of an Obsidian memory file, creating the file or section if missing and skipping exact duplicates so retries are safe.MIT