"Sanity" matching MCP servers:

Gives AI agents direct access to content projects for running GROQ queries, creating, patching, publishing, and unpublishing documents, inspecting and deploying schemas and hosted Studios, and fetching always-current agent rules. Authentication is handled through OAuth or bearer tokens, so no local files or manual token setup are needed.

Deterministic JSON validation and repair for AI agents. Validates, repairs, schema-checks, and diffs JSON so long-running agents don't corrupt their session state with malformed writes.

A self-hosted Sanity MCP server with full CRUD, atomic transactions, reference tracking, and advanced tools for content management and operations.

Connect your Sanity content to AI agents. Create, update, and explore structured content using Claude, Cursor, and VS Code via the Model Context Protocol. Transform content operations from complex queries to simple conversations—giving your team superpowers without sacrificing structure.

Enables AI agents to directly interact with Sanity CMS projects, including querying, creating, and managing documents, schemas, releases, and image generation.

MCP server for uploading local images to Sanity CMS. Enables AI assistants to upload files from your filesystem directly into Sanity as image assets.

An MCP server that enables Claude Desktop to interact with Sanity.io content, providing tools to create, edit, list documents and get schema templates.

Enables semantic retrieval over a structured Quran and classical exegesis library, returning relevant source chunks and verified references for thematic research queries.

Scans repositories for owner identifiers and secrets, blocking pushes or CI merges if any are found.

Enables evaluation of digital marketplaces by classifying demand signals, scoring commercial viability, sanity-checking claims, and comparing candidate channels.

Screens the counterparty of an x402 payment before an agent pays it. One tool, screen_payment, checks address sanity, dynamic-payTo swaps, transport safety and your spend policy, then returns allow / review / block with the reasons — advisory only, and by default it runs with no key, no account and no network call.

Enables LLM agents to query live Wildberries marketplace data — product search with pages, sorting, price filters, per-article ratings and reviews, weekly price history, and seller legal details — with honest, sanity-checked answers and automatic anti-bot handling.

Enables AI agents to check the health of internet infrastructure and specific services, helping diagnose whether issues are local or external.

Gives AI assistants read-only, key-free access to Sentinel-2 NDVI time series, ESA WorldCover land-cover shares, and Copernicus 30 m elevation and slope for a point or small area, returning the scene IDs, units, and caveats behind every number. Built-in sanity checks and a verify tool recompute key values through an independent path so the assistant can flag cloudy, low-confidence, or mismatched results instead of guessing.

Enables AI assistants to read an open laser project through LightBurn's local REST API, explain and sanity-check cut settings, change them by natural-language sentence, apply material-library entries, and drop generated SVGs onto the workspace. It also exposes machine state, position, overrides, and the loaded camera overlay for review, while never starting or stopping a job.

An MCP server that gives AI agents the ability to observe and understand images via multi-provider vision, object detection, hierarchical analysis, and color extraction.

MCP server for discovering, triaging, and monitoring arXiv papers with transparent interest modeling and inspectable ranking.

Enables AI agents to research, create, optimize, publish, and track content using the Frase content operating system, integrating directly with WordPress, Sanity, Webflow, Wix, and FraseCMS.

An MCP server that provides live fair-market-value price comparisons and Ed25519 signed-receipt verification for x402/MPP services, enabling agents to sanity-check quotes and verify receipts.

Enables AI agents to search, browse and sanity-check conference schedules — including co-located events and the Maintainer Summit — with tools for finding sessions and speakers, seeing what's on now, and checking an agenda for overlaps and venue changes. It is read-only, token-efficient, and can be pointed at any Sessionize-published event.

Fans out queries to multiple independent free LLMs from different providers and returns their answers side by side, enabling sanity-checking of decisions or getting multiple perspectives during coding sessions.

Enables AI assistants to grind Solana vanity addresses locally via WebAssembly, compute exact Base58 difficulty, verify proof-of-grind certificates, appraise rarity, and perform non-custodial split-key delegation.

An MCP server that lets Claude Code or any MCP client hand bounded work — code review, boilerplate, commit messages, format conversion, embeddings — to a local GPU model, an OpenAI-compatible endpoint, a router, or a cheap cloud API, so those files never enter the orchestrator's context window. This cuts token spend and quota use while providing a second model to sanity-check results.

Enables LLM agents to safely query educational administration databases through read-only MCP tools, enforcing SQL whitelisting, automatic LIMIT caps, parameterized queries, timeouts, token authentication, and audit logging.

Enables e-commerce customer service agents to retrieve product catalog and return/delivery policy documents through multi-source RAG with RRF fusion, exposing product_search and policy_qa tools for grounded, cited responses.

Enables security teams to determine which ATT&CK techniques lose detection coverage when telemetry sources are removed, by computing set differences over a Sanity content graph and consulting a knowledge base via two Context MCP endpoints.

Enables natural-language querying of PostgreSQL databases with schema grounding and self-correcting error recovery. Provides a live audit trace and verifies results through exploratory decomposition and empty-result sanity checks.

Lets an MCP client hand bounded work such as code review, boilerplate, commit messages, format conversion or embeddings to a local or cloud OpenAI-compatible LLM, so file contents never enter the orchestrating model's context and token costs drop. It also provides a second model to sanity-check code and drafts while the main assistant keeps planning and tool use.