{"data":{"slug":"zcaceres-markdownify-mcp","name":"markdownify-mcp","tagline":"A Model Context Protocol server for converting content into Markdown","github_url":"https://github.com/zcaceres/markdownify-mcp","owner":"zcaceres","repo":"markdownify-mcp","owner_avatar_url":"https://avatars.githubusercontent.com/u/10032979?v=4","primary_language":"TypeScript","stars":2994,"forks":255,"topics":["ai","anthropic","anthropic-ai","anthropic-claude","markdown","mcp","model-context-protocol","ocr","tools"],"archived":false,"github_pushed_at":"2026-09-14T05:23:16+00:00","maintenance_label":"Very active","stars_delta_30d":105,"url":"https://www.graphcanon.com/tools/zcaceres-markdownify-mcp","markdown_url":"https://www.graphcanon.com/tools/zcaceres-markdownify-mcp.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/zcaceres-markdownify-mcp","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=zcaceres-markdownify-mcp","description":"A Model Context Protocol server for converting almost anything to Markdown","homepage_url":null,"license":"MIT","open_issues":29,"watchers":10,"ai_summary":"Converts various inputs to Markdown using the Model Context Protocol.","readme_excerpt":"## Getting Started\n\n1. Clone this repository\n2. Install dependencies:\n   ```\n   bun install\n   ```\n\n   The `preinstall` step creates a Python virtual environment at `.venv` and installs `markitdown[all]`.\n\n3. Build the project:\n   ```\n   bun run build\n   ```\n4. Start the server:\n   ```\n   bun start\n   ```\n\n---\n\n## Usage with Docker\n\nBuild and run:\n```sh\ndocker build -t markdownify-mcp .\ndocker run --rm -i \\\n  -v \"$HOME/Documents:/data:ro\" \\\n  -e MD_ALLOWED_PATHS=/data \\\n  markdownify-mcp\n```\n\nNotes for the Docker MCP catalog (`mcp/markdownify`):\n- Mount any host directories you want the server to read into the container, then pass the **container** paths to the tools (e.g. `/data/foo.pdf`, not `/Users/you/Documents/foo.pdf`).\n- Set `MD_ALLOWED_PATHS` to the colon-separated list of mounted directories so the server enforces a read boundary that matches the bind mount.\n- The published Docker image installs `markitdown[pdf]` only — audio transcription and image OCR (`audio-to-markdown`, `image-to-markdown`) require the `[all]` extras and will fail in the slim image. Use the local install (`bun install`) for the full feature set.\n\n---\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.","github_created_at":"2024-12-18T21:14:52+00:00","created_at":"2026-07-11T11:50:50.441675+00:00","updated_at":"2026-09-20T06:40:38.5701+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"anthropic","name":"anthropic"},{"slug":"markdown","name":"markdown"},{"slug":"ocr","name":"ocr"}],"trust":{"provenance":{"is_fork":false,"github_id":905450127,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T03:52:40.086Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":5,"last_release_at":"2026-05-01T21:05:36Z","stars_delta_30d":105,"open_issues_delta_30d":4},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-26T04:00:27.346Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"mcp":{"source":"package.json:@modelcontextprotocol/*","observed_at":"2026-09-20T03:52:41.107Z","server_manifest":true},"scan":{"source":"repo_scan","observed_at":"2026-09-20T03:52:41.107Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-20T03:52:41.107Z","managed_saas":false},"has_cli":{"value":true,"source":"package.json:bin|scripts","observed_at":"2026-09-20T03:52:41.107Z"},"languages":{"value":["typescript","javascript","python"],"source":"github.language+package.json+pyproject.toml","observed_at":"2026-09-20T03:52:41.107Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-20T03:52:41.107Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-20T03:52:41.107Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"markdownify-mcp is free-to-use software distributed under the MIT License, making no charges beyond those associated with hosting its dependencies if applicable."},"requirements":{"min_ram_gb":null,"requires_docker":false},"constraints":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"when_to_use":["Use markdownify-mcp if you specifically require the Model Context Protocol (MCP) approach to convert content into Markdown and are developing within a TypeScript environment.","If your project includes OCR data that needs conversion into structured Markdown, consider markdownify-mcp for its specialized handling of this task."],"when_not_to_use":["Avoid markdownify-mcp if you need an all-language support as the tool is specifically designed for TypeScript projects and may necessitate additional configuration in other language ecosystems.","Do not use markdownify-mcp when looking for a general text-to-Markdown converter that lacks the MCP framework integration, as this could lead to unnecessary complexity."],"source":"enrich:decision_facts","observed_at":"2026-07-16T21:13:20.680Z"},"constraint_facets":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - markdownify-mcp is free-to-use software distributed under the MIT License, making no charges beyond those associated with hosting its dependencies if applicable."},{"label":"Adopt for","value":"markdownify-mcp is a TypeScript tool serving the Model Context Protocol for generating Markdown from various inputs."},{"label":"License detail","value":"The MIT license applies to markdownify-mcp under which it is released freely with permissive rights for reuse and modification."}]}}