{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_e3qvcg6qgd6a","handle":"iflow-mcp-groundlight-mcp-vision","url":"https://wellknown.network/agents/iflow-mcp-groundlight-mcp-vision","links":{"self":"https://wellknown.network/agents/iflow-mcp-groundlight-mcp-vision/record.json","html":"https://wellknown.network/agents/iflow-mcp-groundlight-mcp-vision","markdown":"https://wellknown.network/agents/iflow-mcp-groundlight-mcp-vision/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-groundlight-mcp-vision","status":"https://wellknown.network/api/v1/agents/iflow-mcp-groundlight-mcp-vision/status","claim":"https://wellknown.network/agents/iflow-mcp-groundlight-mcp-vision/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-groundlight-mcp-vision/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-groundlight-mcp-vision/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-groundlight-mcp-vision/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-groundlight-mcp-vision/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-groundlight-mcp-vision","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_groundlight-mcp-vision","summary":"Allow VLMs to call dedicated specialist CV models","description":"<p align=\"center\">\n<img src=\"images/image0_and_claude_zoomed_in.png\">\n</p>\n\n<p align=\"center\">\n  <a href=\"https://opensource.org/licenses/MIT\">\n    <img src=\"https://img.shields.io/badge/License-MIT-yellow?style=for-the-badge\" alt=\"License: MIT\">\n  <a href=\"https://www.groundlight.ai/blog/vision-as-mcp-service\">\n    <img src=\"https://img.shields.io/badge/Read%20More-Blog-orange?style=for-the-badge\"  alt=\"Read More\">\n  </a>\n</p>\n  </a>\n</p>\n\n# mcp-vision by <img src=\"images/gl_logo.png\" height=25>\n\nA Model Context Protocol (MCP) server exposing HuggingFace computer vision models such as zero-shot object detection as tools, enhancing the vision capabilities of large language or vision-language models.\n\nThis repo is in active development. See below for details of currently available tools.\n\n## Installation\n\nClone the repo:\n```bash\ngit clone git@github.com:groundlight/mcp-vision.git\n```\n\nBuild a local docker image:\n```bash\ncd mcp-vision\nmake build-docker\n```\n\n## Configuring Claude Desktop\n\nAdd this to your `claude_desktop_config.json`:\n\nIf your local environment has access to a NVIDIA GPU:\n```json\n\"mcpServers\": {\n  \"mcp-vision\": {\n    \"command\": \"docker\",\n    \"args\": [\"run\", \"-i\", \"--rm\", \"--runtime=nvidia\", \"--gpus\", \"all\", \"mcp-vision\"],\n \"env\": {}\n  }\n}\n```\nOr, CPU only:\n```json\n\"mcpServers\": {\n  \"mcp-vision\": {\n    \"command\": \"docker\",\n    \"args\": [\"run\", \"-i\", \"--rm\", \"mcp-vision\"],\n \"env\": {}\n  }\n}\n```\nWhen running on CPU, the default large-size object detection model make take a long time to laod and run inference. Consider using a smaller model as `DEFAULT_OBJDET_MODEL` (you can tell Claude directly to use a specific model too). \n\n**(Beta)** It is possible to run the public docker image directly without building locally, however the download time may interfere with Claude's loading of the server. \n```json\n\"mcpServers\": {\n  \"mcp-vision\": {\n    \"command\": \"docker\",\n    \"args\": [\"run\", \"-i\", \"--rm\", \"--runtime=nvidia\", \"--gpus\", \"all\", \"groundlight/mcp-vision:late…","publisher":{"name":"Groundlight AI","url":null},"homepage":null,"repository":null,"version":"0.1.2","license":"MIT License","protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_groundlight-mcp-vision","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","summary":"pypi","version":"pypi","description":"pypi","publisherName":"pypi"}},"derived":{"capabilities":[{"slug":"media.image-understanding","name":"Image Understanding","confidence":1,"provenance":"derived"},{"slug":"ai.model-access","name":"Model Access","confidence":0.905,"provenance":"derived"},{"slug":"dev.version-control","name":"Version Control","confidence":0.745,"provenance":"derived"}],"categories":["ai","dev","media"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_groundlight-mcp-vision","registry":"pypi","observedAt":"2026-09-15T18:21:48.208Z","publishedAt":"2026-02-13T13:18:55.565520Z","latestVersion":"0.1.2"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_groundlight-mcp-vision","url":"https://pypi.org/project/iflow-mcp_groundlight-mcp-vision/","firstSeenAt":"2026-09-09T19:23:22.335Z","fetchedAt":"2026-09-15T18:19:51.854Z","normalizedAt":"2026-09-15T18:19:51.854Z"}]},"firstSeenAt":"2026-09-09T19:23:22.335Z","updatedAt":"2026-09-15T18:21:48.208Z"}