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The bridge layer implements protocol translation that maps OpenAPI endpoint specifications, parameter schemas, and response types to MCP tool definitions without requiring manual schema rewriting, allowing existing OpenAPI servers to be consumed by MCP clients and MCP tools to be exposed as REST APIs.","intents":["I want to use my existing OpenAPI servers with MCP-based LLM agents without rewriting tool definitions","I need to expose MCP tool servers as REST APIs for integration with non-MCP systems","I want to avoid vendor lock-in by supporting both OpenAPI and MCP protocols simultaneously"],"best_for":["Teams building LLM agent systems that need to integrate both legacy REST APIs and modern MCP tools","Developers migrating from REST-only tooling to MCP without abandoning existing OpenAPI infrastructure","Organizations requiring protocol-agnostic tool server deployments"],"limitations":["Bidirectional translation may lose protocol-specific features (e.g., OpenAPI security schemes not fully representable in MCP schema)","Real-time streaming responses in OpenAPI may not map cleanly to MCP's request-response model","Complex nested schemas with circular references require manual intervention"],"requires":["Python 3.9+","FastAPI framework for OpenAPI server implementations","MCP SDK for Python","Valid OpenAPI 3.0+ specification or MCP tool schema"],"input_types":["OpenAPI specification (JSON/YAML)","MCP tool schema (JSON)","REST endpoint definitions"],"output_types":["MCP tool definitions (JSON)","OpenAPI server implementations (Python/FastAPI)","Protocol adapter code"],"categories":["tool-use-integration","protocol-bridging"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_1","uri":"capability://code.generation.editing.fastapi.based.openapi.server.generation.from.specifications","name":"fastapi-based openapi server generation from specifications","description":"Generates production-ready FastAPI server implementations directly from OpenAPI specifications, automatically creating endpoint handlers, request/response validation, and OpenAPI documentation. 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The authentication system integrates with FastAPI's security schemes, validates credentials on every request, and enforces HTTPS for production deployments, protecting tool server communications and preventing unauthorized access.","intents":["I want my tool servers to use HTTPS encryption for secure communication","I need to authenticate LLM agents and control which agents can access which servers","I want to use standard HTTP authentication methods without custom security code"],"best_for":["Production LLM agent systems requiring secure tool server communication","Multi-tenant environments where agents need authentication and authorization","Organizations with security requirements for API access control"],"limitations":["Certificate management requires manual renewal or external automation (e.g., Let's Encrypt)","API key rotation requires server restart; no hot-reload of credentials","OAuth2 implementation requires external identity provider; no built-in user management","Rate limiting not included; requires external API gateway for request throttling","No built-in audit logging of authentication attempts or access patterns"],"requires":["Python 3.9+","FastAPI server instance","SSL/TLS certificates for HTTPS (self-signed or CA-signed)","Authentication credentials (API keys, OAuth2 provider, etc.)"],"input_types":["SSL/TLS certificate files (PEM format)","Authentication credentials (API keys, tokens, passwords)","Security scheme definitions (JSON)"],"output_types":["HTTPS-encrypted connections","Authentication validation results (authenticated/denied)","Security headers in responses"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_2","uri":"capability://tool.use.integration.filesystem.operations.tool.server.with.sandboxed.access.control","name":"filesystem operations tool server with sandboxed access control","description":"Provides a dedicated OpenAPI server that exposes filesystem operations (read, write, list, delete) with configurable path-based access control and sandboxing to prevent directory traversal attacks. The filesystem server implements allowlist-based path restrictions, validates all file operations against configured boundaries, and provides atomic operations with error handling for permission violations, enabling LLM agents to safely interact with the local filesystem without unrestricted access.","intents":["I want my LLM agent to read and write files safely without access to sensitive system directories","I need to restrict which directories an agent can access based on project boundaries","I want atomic file operations with proper error handling and permission validation"],"best_for":["LLM agents that need controlled filesystem access for code generation or data processing","Multi-tenant systems where agents must be isolated to specific directory trees","Development environments where agents need to modify project files safely"],"limitations":["Symbolic link handling requires explicit configuration to prevent escape attacks","No built-in file locking mechanism for concurrent access from multiple agents","Large file operations (>100MB) may cause memory pressure without streaming support","Permission model is path-based only; cannot enforce fine-grained file attribute restrictions"],"requires":["Python 3.9+","FastAPI server instance","Filesystem read/write permissions for configured directories","Configuration file specifying allowed directory paths"],"input_types":["File paths (string)","File content (text/binary)","Directory paths for listing","JSON configuration for access control"],"output_types":["File content (text/binary)","Directory listings (JSON)","Operation status (success/error)","File metadata (size, modified time, permissions)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_3","uri":"capability://memory.knowledge.memory.and.knowledge.graph.server.with.structured.storage","name":"memory and knowledge graph server with structured storage","description":"Provides an OpenAPI server for storing, retrieving, and querying structured knowledge with graph-based relationships between entities. The memory server implements a knowledge graph backend that supports entity creation, relationship definition, and graph traversal queries, enabling LLM agents to maintain persistent context across conversations and build semantic relationships between stored information without requiring external database setup.","intents":["I want my LLM agent to remember facts and relationships across multiple conversations","I need to query related information based on semantic connections, not just keyword matching","I want to build a knowledge base that grows as the agent learns new information"],"best_for":["Long-running LLM agents that need persistent memory across sessions","Multi-turn conversation systems requiring context accumulation","Knowledge management systems where semantic relationships matter more than keyword search"],"limitations":["Graph traversal queries may become slow with >100k entities without proper indexing","No built-in full-text search; keyword queries require external search layer","Memory persistence requires external storage backend (not included in server)","Circular relationship handling requires explicit cycle detection logic","No automatic deduplication of semantically similar entities"],"requires":["Python 3.9+","FastAPI server instance","Graph database or in-memory graph library (e.g., NetworkX)","Persistent storage backend for knowledge graph state"],"input_types":["Entity definitions (JSON with properties)","Relationship definitions (source, target, relationship type)","Graph query specifications (traversal depth, filters)"],"output_types":["Entity records (JSON)","Relationship lists (JSON)","Graph traversal results (JSON with path information)","Query results with entity metadata"],"categories":["memory-knowledge","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_4","uri":"capability://tool.use.integration.weather.data.retrieval.server.with.real.time.api.integration","name":"weather data retrieval server with real-time api integration","description":"Exposes a standardized OpenAPI interface for weather data queries that abstracts underlying weather API providers (e.g., OpenWeatherMap, WeatherAPI) and caches responses to reduce API calls. The weather server implements provider abstraction with configurable backends, automatic response caching with TTL-based invalidation, and unified response schemas across different weather data sources, allowing LLM agents to query weather information without managing multiple API credentials or handling provider-specific response formats.","intents":["I want my LLM agent to access current weather and forecasts without managing multiple weather API credentials","I need consistent weather data responses regardless of which underlying weather provider is configured","I want to reduce weather API costs through intelligent response caching"],"best_for":["LLM agents that need weather context for decision-making or recommendations","Multi-agent systems where weather data is queried frequently across different locations","Applications requiring weather integration without direct API management"],"limitations":["Cache TTL is fixed; no dynamic cache invalidation based on weather change severity","Limited to weather data providers with public APIs; proprietary weather services not supported","Forecast accuracy depends on underlying provider; no ensemble forecasting across providers","Geographic coverage limited to provider's supported regions","Real-time severe weather alerts not included; only standard forecast data"],"requires":["Python 3.9+","FastAPI server instance","API key for at least one supported weather provider (OpenWeatherMap, WeatherAPI, etc.)","Network access to weather provider APIs"],"input_types":["Location (latitude/longitude or city name)","Query type (current weather, forecast, historical)","Time range for forecasts (optional)"],"output_types":["Weather data (JSON with temperature, conditions, humidity, wind speed)","Forecast data (JSON with hourly/daily predictions)","Cache status metadata"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_5","uri":"capability://tool.use.integration.git.repository.operations.server.with.version.control.integration","name":"git repository operations server with version control integration","description":"Provides an OpenAPI server that exposes Git operations (clone, commit, push, pull, branch management) through a standardized REST interface, enabling LLM agents to interact with version control systems without requiring Git CLI knowledge or local repository setup. The Git server implements repository state management, safe command execution with validation, and atomic operations for multi-step workflows like commit-and-push, abstracting Git's complexity behind simple REST endpoints.","intents":["I want my LLM agent to commit code changes to a repository without understanding Git CLI","I need safe Git operations that validate commands before execution to prevent repository corruption","I want to enable agents to manage branches, create commits, and push changes in a single workflow"],"best_for":["Code generation agents that need to persist generated code to version control","CI/CD automation systems where agents need to manage repository state","Development workflows where agents collaborate with human developers through Git"],"limitations":["Complex merge conflict resolution requires manual intervention; server cannot auto-resolve conflicts","Large repository operations (>1GB) may timeout without streaming support","SSH key management requires secure credential storage outside the server","No support for Git submodules or worktrees","Rebasing and cherry-picking operations not supported; only linear commit history"],"requires":["Python 3.9+","FastAPI server instance","Git installed on server system","SSH keys or credentials for repository access","Repository URL and access permissions"],"input_types":["Repository URL (HTTPS or SSH)","Commit messages (text)","File paths and content for changes","Branch names (string)","Git credentials (SSH keys or tokens)"],"output_types":["Commit hashes (string)","Branch information (JSON with branch names and HEAD commits)","Diff output (unified diff format)","Repository status (JSON with staged/unstaged changes)","Push/pull operation results (success/error)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_6","uri":"capability://tool.use.integration.user.information.and.profile.management.server","name":"user information and profile management server","description":"Exposes an OpenAPI server for managing user profiles, preferences, and metadata with role-based access control and data validation. The user info server implements user CRUD operations, preference storage with schema validation, and role-based authorization checks on all operations, enabling LLM agents to access and manage user context safely while respecting permission boundaries and data privacy constraints.","intents":["I want my LLM agent to access user profile information to personalize responses","I need to store user preferences that persist across agent interactions","I want to enforce role-based access control so agents can only access authorized user data"],"best_for":["Multi-user LLM agent systems requiring personalization and user context","Applications with role-based access control where agents must respect user permissions","Systems managing user preferences and profile data across multiple agent interactions"],"limitations":["No built-in encryption for sensitive user data; requires external encryption layer","Role-based access control is simple (role-per-user); no fine-grained attribute-based access control","No audit logging of user data access; cannot track which agents accessed which user information","Preference schema validation is static; dynamic schema changes require server restart","No built-in data retention policies or GDPR-compliant deletion workflows"],"requires":["Python 3.9+","FastAPI server instance","User database or persistent storage backend","Role definitions and access control configuration"],"input_types":["User identifiers (string/UUID)","Profile data (JSON with name, email, contact info)","Preference objects (JSON with user-specific settings)","Role assignments (string role names)"],"output_types":["User profile records (JSON)","Preference data (JSON)","Role information (JSON with permissions)","Access control validation results (allowed/denied)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_7","uri":"capability://tool.use.integration.time.and.timezone.aware.scheduling.server","name":"time and timezone-aware scheduling server","description":"Provides an OpenAPI server for time-based operations including timezone conversion, scheduling queries, and time-aware calculations, enabling LLM agents to work with time data correctly across different timezones and locales. The time server implements timezone-aware datetime handling, cron expression parsing for schedule definitions, and time arithmetic operations, abstracting timezone complexity and allowing agents to reason about time without managing timezone databases or calendar calculations manually.","intents":["I want my LLM agent to understand time correctly across different user timezones","I need to parse and validate cron expressions for scheduling tasks","I want to perform time arithmetic (add days, convert timezones) without timezone bugs"],"best_for":["Global LLM agent systems serving users across multiple timezones","Scheduling and automation systems where agents need to interpret time expressions","Applications requiring accurate time calculations with timezone awareness"],"limitations":["Daylight saving time transitions may cause ambiguity in time calculations near DST boundaries","Cron expression support is limited to standard 5-field format; no extended formats (e.g., seconds field)","No support for business day calculations or holiday calendars","Timezone database updates require server restart; no dynamic timezone updates","Leap second handling not implemented; assumes standard 86400-second days"],"requires":["Python 3.9+","FastAPI server instance","Python tzdata library for timezone information","Cron expression parser library (e.g., croniter)"],"input_types":["Datetime strings (ISO 8601 format)","Timezone identifiers (IANA timezone names)","Cron expressions (string)","Time deltas (duration specifications)"],"output_types":["Datetime values (ISO 8601 JSON)","Timezone information (JSON with offset, DST status)","Cron schedule information (JSON with next execution times)","Time arithmetic results (duration or datetime)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_8","uri":"capability://automation.workflow.docker.compose.based.multi.server.orchestration.and.deployment","name":"docker compose-based multi-server orchestration and deployment","description":"Provides a Docker Compose configuration that orchestrates deployment of multiple OpenAPI tool servers as containerized services with networking, environment configuration, and service discovery. The deployment system uses Docker Compose to manage server lifecycle, configure inter-service communication, expose ports, and manage environment variables, enabling developers to deploy the entire tool server ecosystem with a single command without manual container management or networking setup.","intents":["I want to deploy multiple tool servers together without managing individual Docker containers","I need the servers to communicate with each other through service discovery","I want to configure all servers with environment variables in a single deployment file"],"best_for":["Development teams deploying local LLM agent environments with multiple tool servers","Docker-based CI/CD pipelines that need to spin up tool server infrastructure","Rapid prototyping of LLM agent systems with multiple integrated tools"],"limitations":["Docker Compose is not suitable for production multi-node deployments; requires Kubernetes for scaling","No built-in health checks or automatic restart policies; requires manual configuration","Service discovery is limited to Docker's internal DNS; external service discovery not supported","Volume management is basic; complex data persistence requires external storage configuration","No built-in monitoring, logging aggregation, or metrics collection"],"requires":["Docker 20.10+","Docker Compose 2.0+","Docker daemon running on deployment host","Sufficient disk space for container images (~500MB per server)"],"input_types":["Docker Compose YAML configuration","Environment variable definitions (.env files)","Service port mappings","Volume mount specifications"],"output_types":["Running Docker containers","Service network with inter-container communication","Exposed ports for external access","Container logs and status information"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-open-webui-openapi-servers__cap_9","uri":"capability://safety.moderation.openapi.specification.validation.and.schema.conformance.checking","name":"openapi specification validation and schema conformance checking","description":"Validates OpenAPI specifications against the OpenAPI 3.0+ standard and checks that server implementations conform to their declared specifications, ensuring consistency between API documentation and actual behavior. The validation system parses OpenAPI specs, validates schema correctness, checks endpoint implementations against declared parameters and responses, and reports conformance issues, enabling developers to catch specification-implementation mismatches before deployment.","intents":["I want to validate my OpenAPI specifications are correct before deploying servers","I need to ensure my server implementations match their OpenAPI declarations","I want to catch schema errors and missing endpoint implementations early"],"best_for":["Development teams building OpenAPI-based tool servers who want quality assurance","CI/CD pipelines that need to validate specifications before deployment","Organizations standardizing on OpenAPI with automated compliance checking"],"limitations":["Validation is static; cannot detect runtime behavior mismatches (e.g., incorrect error codes)","Complex schema validation (discriminators, polymorphism) may require manual review","No support for OpenAPI extensions or vendor-specific fields","Conformance checking requires running server instances; cannot validate offline","Performance validation (latency, throughput) not included; only structural validation"],"requires":["Python 3.9+","OpenAPI specification (JSON/YAML)","Running server instances for conformance checking","OpenAPI validator library (e.g., openapi-spec-validator)"],"input_types":["OpenAPI specification files (JSON/YAML)","Server endpoint URLs for conformance testing","Test request/response examples"],"output_types":["Validation report (JSON with errors and warnings)","Conformance test results (pass/fail per endpoint)","Schema compliance metrics"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":38,"verified":false,"data_access_risk":"high","permissions":["Python 3.9+","FastAPI framework for OpenAPI server implementations","MCP SDK for Python","Valid OpenAPI 3.0+ specification or MCP tool schema","FastAPI 0.95+","Pydantic 2.0+","Valid OpenAPI 3.0+ specification","FastAPI server instances","Shared error schema definition (JSON Schema)","Error code enumeration"],"failure_modes":["Bidirectional translation may lose protocol-specific features (e.g., OpenAPI security schemes not fully representable in MCP schema)","Real-time streaming responses in OpenAPI may not map cleanly to MCP's request-response model","Complex nested schemas with circular references require manual intervention","Generated servers require custom business logic implementation in handler functions","Complex OpenAPI features like discriminators and polymorphic schemas may require manual adjustment","Performance overhead from Pydantic validation on every request (~5-10ms per request)","Limited support for streaming responses and WebSocket connections","Standardized error format may lose server-specific error details; requires custom error mapping","HTTP status codes may not perfectly map to semantic error categories","Nested error information (e.g., validation errors for multiple fields) requires custom formatting","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.435515431725399,"quality":0.34,"ecosystem":0.48999999999999994,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.065Z","last_scraped_at":"2026-05-03T14:23:44.761Z","last_commit":"2025-09-25T20:35:01Z"},"community":{"stars":944,"forks":166,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-open-webui-openapi-servers","compare_url":"https://unfragile.ai/compare?artifact=mcp-open-webui-openapi-servers"}},"signature":"qIlC6Rz/jmvTXvl6se9gTitRZ2mg53az082sXU3/j3jqQSv00hh3Td4MKoMiOyE/Kbk2yHCsoa8xMJG0IB1iDQ==","signedAt":"2026-06-21T06:20:39.035Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-open-webui-openapi-servers","artifact":"https://unfragile.ai/mcp-open-webui-openapi-servers","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-open-webui-openapi-servers","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}