{"id":"ricardo-m-l-mcp-ocr-server","name":"mcp-ocr-server","homepage":null,"repo_url":"https://github.com/Ricardo-M-L/mcp-ocr-server","category":"ai-ml","subcategories":[],"tags":["mcp","ocr","tesseract","opencv","gocv","preprocessing","local-ai-tooling"],"what_it_does":"Provides an MCP (Model Context Protocol) server for OCR on images using Tesseract OCR and GoCV/OpenCV, including configurable and auto image preprocessing (quality analysis, denoising, thresholding, deskew, contrast/brightness adjustments), worker pooling, and result caching keyed by SHA256.","use_cases":["Extracting text from scanned documents/images","OCR for mixed-language content (eng/chi_sim/chi_tra/jpn)","Batch OCR for multiple images","Integrating OCR as an MCP tool for local/desktop assistants (e.g., Claude Desktop)"],"not_for":["Real-time OCR at very high throughput without resource tuning","Environments requiring strong transport/authentication controls at the MCP layer (no auth described)","Use cases that require an HTTP/REST contract or webhooks"],"best_when":"You want a locally run OCR capability exposed via MCP tools with preprocessing and caching for repeated inputs.","avoid_when":"You need a documented authentication/authorization model, rate-limit guarantees, or a publicly hosted multi-tenant API.","alternatives":["Run Tesseract CLI directly and build a thin wrapper","Use an OCR API from a managed provider (e.g., Google Vision, AWS Textract, Azure OCR)","Use existing OCR libraries/frameworks with a REST API wrapper"],"af_score":65.8,"security_score":30.0,"reliability_score":26.2,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-04-04T21:22:12.048105+00:00","interface":{"has_rest_api":false,"has_graphql":false,"has_grpc":false,"has_mcp_server":true,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":[],"oauth":false,"scopes":false,"notes":"No authentication/authorization mechanism is described in the provided README for the MCP server."},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"Self-hosted open-source project; costs are infrastructure-dependent."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":65.8,"security_score":30.0,"reliability_score":26.2,"mcp_server_quality":78.0,"documentation_accuracy":70.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":100.0,"rate_limit_clarity":10.0,"tls_enforcement":40.0,"auth_strength":10.0,"scope_granularity":0.0,"dependency_hygiene":50.0,"secret_handling":60.0,"security_notes":"No auth/authorization is documented for the MCP server. The server processes images provided by users/agents; ensure you control file path access and sanitize/limit input sizes (max_image_size exists). TLS guarantees for MCP transport are not described.","uptime_documented":0.0,"version_stability":35.0,"breaking_changes_history":20.0,"error_recovery":50.0,"idempotency_support":"true","idempotency_notes":"OCR operations are effectively idempotent for the same input (especially with SHA256-based caching), but the README does not explicitly document idempotency guarantees.","pagination_style":"none","retry_guidance_documented":false,"known_agent_gotchas":["Tool inputs include local file paths (image_path); agents must ensure the MCP server has access to those paths.","Base64 OCR may be large; ensure payload sizes and server-side max image limits are respected (max_image_size configurable).","OCR performance depends on worker_pool_size, cache settings, and preprocessing configuration; misconfiguration can cause latency or memory pressure.","Tesseract language data must exist at data_path/tessdata; missing languages will fail requests."]}}