{"id":"neelkamath-spacy-server","name":"spacy-server","homepage":"https://hub.docker.com/r/neelkamath/spacy-server","repo_url":"https://hub.docker.com/r/neelkamath/spacy-server","category":"ai-ml","subcategories":[],"tags":["nlp","spacy","microservice","http-api","entity-extraction","linguistics"],"what_it_does":"spacy-server is a service wrapper for spaCy that exposes spaCy NLP capabilities over a network interface (typically as an HTTP API) so other applications can send text and receive NLP annotations.","use_cases":["Named entity recognition and information extraction via a networked service","Tokenization/lemmatization/POS tagging as a shared backend","Document processing pipelines where a separate NLP microservice is preferred","Consistent NLP inference across multiple apps/environments"],"not_for":["Latency-sensitive in-process NLP where embedding spaCy directly is simpler","Highly specialized models without provisioning/serving configuration","Use cases requiring strong built-in governance (tenant-level controls, audit logs) if not documented"],"best_when":"You want to run spaCy models once and serve results to multiple clients via a simple backend API.","avoid_when":"You cannot verify the exact API/auth/error-handling semantics from the provided documentation or need enterprise-grade security controls beyond what’s documented.","alternatives":["Direct spaCy usage in Python (run locally in-process)","FastAPI/Starlette wrappers around spaCy (custom service)","Elasticsearch ingest pipelines with NLP processors (when applicable)","Hugging Face inference endpoints (for transformer-based NLP)"],"af_score":38.8,"security_score":45.5,"reliability_score":33.8,"package_type":"mcp_server","discovery_source":["docker_mcp"],"priority":"low","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-04-04T21:26:43.425591+00:00","interface":{"has_rest_api":true,"has_graphql":false,"has_grpc":false,"has_mcp_server":false,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":["Unknown (not provided in prompt)"],"oauth":false,"scopes":false,"notes":"No authentication details were provided in the supplied content, so auth method/strength cannot be confirmed."},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"No pricing information provided; as a library/service wrapper it is typically self-hosted."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":38.8,"security_score":45.5,"reliability_score":33.8,"mcp_server_quality":0.0,"documentation_accuracy":40.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":60.0,"rate_limit_clarity":10.0,"tls_enforcement":60.0,"auth_strength":40.0,"scope_granularity":30.0,"dependency_hygiene":50.0,"secret_handling":50.0,"security_notes":"TLS/auth/scoping/secret-handling are not described in the provided prompt, so scores reflect uncertainty rather than confirmed behavior. As a self-hosted NLP service, the primary risks are exposure of an open inference endpoint and mishandling of deployment secrets/model assets; verify TLS, authentication, and logging practices in the actual repository/docs.","uptime_documented":0.0,"version_stability":50.0,"breaking_changes_history":50.0,"error_recovery":35.0,"idempotency_support":"false","idempotency_notes":null,"pagination_style":"none","retry_guidance_documented":false,"known_agent_gotchas":["You may need to handle model loading/configuration and resource constraints (CPU/RAM) at the service level.","Because API schemas/auth/error formats were not provided here, agents should verify request/response formats and failure modes before automating."]}}