{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-metatool-ai--metamcp","slug":"metatool-ai--metamcp","name":"metamcp","type":"mcp","url":"https://docs.metamcp.com","page_url":"https://unfragile.ai/metatool-ai--metamcp","categories":["mcp-servers"],"tags":["mcp","mcp-gateway","mcp-host","mcp-middleware","mcp-server","mcp-servers","mcp-to-openapi","mcp-tools","model-context-protocol","model-context-protocol-server","model-context-protocol-servers","open-webui","openapi","self-hosted","vibe-coding"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-metatool-ai--metamcp__cap_0","uri":"capability://tool.use.integration.multi.server.mcp.aggregation.with.namespace.based.tool.curation","name":"multi-server mcp aggregation with namespace-based tool curation","description":"Dynamically aggregates tools from multiple MCP servers into isolated namespaces, applying server-to-namespace-to-endpoint three-tier configuration abstraction. Uses a session pool management system that pre-allocates persistent connections to backend MCP servers, eliminating cold-start latency on each client request. The aggregation engine maintains a tool registry synchronized via discovery mechanisms, enabling administrators to selectively expose, override, or filter tools per namespace without modifying upstream servers.","intents":["consolidate tools from 5+ MCP servers into a single curated interface for LLM clients","expose different tool subsets to different teams or applications via namespace isolation","reduce connection overhead by reusing pooled MCP server sessions across multiple client requests","customize tool behavior (rename, modify schema, add metadata) without forking upstream servers"],"best_for":["teams managing multiple MCP servers and needing centralized tool governance","enterprises requiring multi-tenant tool access with per-namespace customization","LLM application builders wanting to abstract away MCP server complexity"],"limitations":["session pool pre-allocation requires upfront memory/connection overhead proportional to pool size","tool discovery synchronization is eventually consistent — newly added tools on upstream servers may have propagation delay","namespace isolation is logical, not cryptographic — relies on authentication layer for true security boundaries"],"requires":["PostgreSQL database for configuration persistence","Docker runtime for containerized deployment","2+ MCP servers accessible via stdio, SSE, or HTTP transports","Node.js 18+ for backend runtime"],"input_types":["MCP server configuration (stdio command, HTTP URL, SSE endpoint)","namespace definitions with tool filtering rules","tool override schemas (name, description, parameter modifications)"],"output_types":["unified MCP server interface exposing aggregated tools","tool registry with metadata and access control annotations","session pool state (active connections, utilization metrics)"],"categories":["tool-use-integration","mcp-gateway"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_1","uri":"capability://tool.use.integration.middleware.pipeline.system.for.tool.transformation.and.filtering","name":"middleware pipeline system for tool transformation and filtering","description":"Applies a composable middleware stack to tool definitions and invocations at the namespace level, enabling schema modification, parameter validation, access control filtering, and request/response transformation without modifying upstream MCP servers. Middleware executes in sequence during tool discovery (for schema transformation) and at invocation time (for request/response interception). The system supports both built-in middleware (filtering, renaming, schema override) and custom middleware via plugin interfaces.","intents":["rename tools or modify their schemas to match organizational naming conventions","filter tools by role or permission level, exposing only authorized tools per namespace","validate or transform tool parameters before sending to upstream servers","intercept and log tool invocations for audit trails or monitoring"],"best_for":["teams needing to standardize tool interfaces across heterogeneous MCP servers","organizations with strict access control requirements per team or role","builders wanting to add observability or validation layers without forking servers"],"limitations":["middleware execution adds latency per pipeline stage — complex pipelines may add 50-200ms per invocation","custom middleware requires TypeScript knowledge and recompilation/redeployment","middleware state is not persisted — stateful transformations require external storage"],"requires":["namespace configuration with middleware definitions","TypeScript for custom middleware development","Docker rebuild for custom middleware deployment"],"input_types":["tool schema definitions (JSON Schema format)","tool invocation requests with parameters","middleware configuration (filter rules, schema overrides, transformation functions)"],"output_types":["transformed tool schemas with modified names, descriptions, parameters","filtered tool lists (subset of original tools based on access rules)","intercepted invocation requests/responses with audit metadata"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_10","uri":"capability://tool.use.integration.nested.metamcp.support.with.tool.name.parsing.and.disambiguation","name":"nested metamcp support with tool name parsing and disambiguation","description":"Supports chaining MetaMCP instances (MetaMCP connecting to another MetaMCP as an MCP server), enabling hierarchical tool aggregation and delegation. When a MetaMCP instance connects to another MetaMCP, it discovers tools from the downstream instance and can aggregate them into its own namespaces. Tool names are parsed to disambiguate which MetaMCP instance a tool belongs to, enabling multi-level tool hierarchies.","intents":["create hierarchical tool aggregation by chaining MetaMCP instances","delegate tool access to downstream MetaMCP instances based on namespace or team","enable multi-level access control by stacking authentication layers","organize tools into logical hierarchies across multiple MetaMCP deployments"],"best_for":["large organizations with multiple teams, each running their own MetaMCP instance","enterprises needing hierarchical access control and tool delegation","teams wanting to aggregate tools from multiple MetaMCP deployments"],"limitations":["nested MetaMCP adds latency due to additional hops — each level adds request/response overhead","tool name disambiguation requires careful naming conventions — ambiguous names can cause routing errors","debugging nested MetaMCP chains is complex — errors may originate from any level in the chain"],"requires":["multiple MetaMCP instances deployed and accessible","tool naming conventions that enable disambiguation (e.g., namespace:tool_name)"],"input_types":["downstream MetaMCP endpoint configuration","tool name parsing rules for disambiguation"],"output_types":["aggregated tools from downstream MetaMCP instances","hierarchical tool registry with multi-level organization"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_11","uri":"capability://automation.workflow.error.handling.and.crash.recovery.with.automatic.reconnection","name":"error handling and crash recovery with automatic reconnection","description":"Implements comprehensive error handling for MCP server failures, network issues, and invalid tool invocations. When an MCP server becomes unreachable, the session pool detects the failure via health checks and automatically reconnects. Tool invocation errors are caught, logged, and returned to clients with detailed error messages. The system distinguishes between transient errors (network timeouts, temporary unavailability) and permanent errors (invalid tool, authentication failure), applying appropriate recovery strategies.","intents":["automatically recover from transient MCP server failures without client intervention","provide detailed error messages to clients for debugging tool invocation failures","log all errors for operational monitoring and alerting","distinguish between transient and permanent errors to apply appropriate recovery strategies"],"best_for":["production deployments requiring high availability and automatic recovery","teams needing detailed error logging for debugging and monitoring","operators wanting to minimize manual intervention for transient failures"],"limitations":["automatic reconnection may mask underlying server issues — operators must monitor reconnection frequency","error messages are propagated from upstream servers — may be cryptic or unhelpful","transient vs permanent error classification is heuristic-based — some errors may be misclassified"],"requires":["health check configuration (interval, timeout, failure threshold)","error logging infrastructure (stdout, file, or external service)"],"input_types":["tool invocation requests","MCP server responses (success or error)"],"output_types":["tool invocation results (success or detailed error)","error logs with timestamp, server, error type, and recovery action"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_12","uri":"capability://automation.workflow.trpc.type.safe.api.procedures.for.configuration.and.management","name":"trpc type-safe api procedures for configuration and management","description":"Implements backend business logic via tRPC procedures, providing end-to-end type safety from frontend UI to database. tRPC procedures handle configuration mutations (create/update/delete MCP servers, namespaces, endpoints), tool discovery, and session management. Type definitions are shared between frontend and backend, eliminating type mismatches and enabling IDE autocomplete for API calls.","intents":["provide type-safe API for configuration management with compile-time type checking","enable IDE autocomplete and type hints for frontend developers","eliminate runtime type mismatches between frontend and backend","simplify API testing by leveraging TypeScript type system"],"best_for":["TypeScript-based teams wanting end-to-end type safety","developers preferring type-safe APIs over REST/GraphQL","teams wanting to reduce API testing overhead via type system"],"limitations":["tRPC is TypeScript-only — non-TypeScript clients cannot use type-safe APIs","tRPC procedures are not self-documenting like REST/GraphQL — API documentation must be maintained separately","tRPC adds a layer of abstraction — debugging requires understanding tRPC internals"],"requires":["TypeScript for frontend and backend","tRPC client library on frontend","tRPC server library on backend"],"input_types":["tRPC procedure calls with typed parameters"],"output_types":["typed responses with compile-time type checking"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_13","uri":"capability://data.processing.analysis.drizzle.orm.data.persistence.with.postgresql.repository.layer","name":"drizzle orm data persistence with postgresql repository layer","description":"Uses Drizzle ORM to define database schema and implement repository layer for all data persistence (MCP server configurations, namespaces, endpoints, tool registry, API keys, audit logs). Drizzle provides type-safe SQL queries with compile-time validation, migrations for schema evolution, and query builders for complex queries. All data is persisted in PostgreSQL, enabling multi-instance deployments with shared state.","intents":["persist all MetaMCP configuration in a relational database for durability and multi-instance sharing","provide type-safe database access with compile-time SQL validation","enable schema evolution via migrations without manual SQL","support complex queries for tool discovery, access control, and audit logging"],"best_for":["production deployments requiring data durability and multi-instance state sharing","teams wanting type-safe database access with compile-time validation","organizations needing audit trails and compliance logging"],"limitations":["PostgreSQL is a hard dependency — no support for other databases (MySQL, SQLite, etc.)","Drizzle migrations must be run manually — no automatic schema evolution","complex queries may require raw SQL — query builder has limitations for advanced use cases"],"requires":["PostgreSQL database (external or containerized)","Drizzle ORM library","database credentials and connection string"],"input_types":["configuration data (MCP servers, namespaces, endpoints, API keys)","tool definitions and overrides","audit log entries"],"output_types":["persisted configuration in PostgreSQL","query results for configuration retrieval and tool discovery"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_2","uri":"capability://tool.use.integration.public.endpoint.exposure.with.multi.protocol.transport.support","name":"public endpoint exposure with multi-protocol transport support","description":"Exposes aggregated MCP servers as public endpoints via three simultaneous transport protocols: Server-Sent Events (SSE) for streaming, Streamable HTTP for request-response, and OpenAPI for REST clients. Each endpoint is independently configurable with its own authentication scheme (API key, OAuth, public), namespace binding, and session lifecycle. The system maintains separate session pools per endpoint, allowing different clients to connect via their preferred protocol without interference.","intents":["expose MCP tools to LLM clients that only support SSE or HTTP transports","provide REST/OpenAPI interface for non-MCP-aware tools or legacy integrations","create public endpoints for specific namespaces while keeping others private","support multiple authentication schemes (API key, OAuth) on different endpoints simultaneously"],"best_for":["teams integrating MCP with diverse client ecosystems (Claude, custom LLM agents, REST clients)","organizations needing to expose internal tools via public APIs with authentication","builders wanting to support both MCP-native and REST-based tool consumption"],"limitations":["OpenAPI endpoint is a projection of MCP tools — not all MCP capabilities (resources, prompts) map to REST","SSE and HTTP endpoints maintain separate session pools, doubling memory overhead vs single protocol","protocol translation adds latency — OpenAPI requests go through schema mapping before reaching MCP servers"],"requires":["HTTP server infrastructure (Node.js/Express backend)","DNS/routing for public endpoint URLs","API key or OAuth provider for authentication (optional for public endpoints)"],"input_types":["endpoint configuration (name, namespace, protocol, authentication scheme)","client requests via SSE, HTTP, or REST/OpenAPI"],"output_types":["SSE stream of MCP messages","HTTP response with tool results","OpenAPI schema and REST responses"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_3","uri":"capability://safety.moderation.api.key.and.oauth.authentication.with.multi.tenant.access.control","name":"api key and oauth authentication with multi-tenant access control","description":"Implements a multi-tenant authentication and authorization layer supporting both API key and OAuth flows, with per-endpoint and per-namespace access control. API keys are stored in PostgreSQL with scoping rules (allowed endpoints, namespaces, tools), and OAuth integrates with external providers via standard OIDC/OAuth2 flows. The system enforces access control at the endpoint level (which clients can connect) and tool level (which tools a client can invoke), with audit logging of all authenticated requests.","intents":["issue API keys to different teams/applications with scoped access to specific namespaces","integrate with corporate OAuth providers (Okta, Azure AD) for SSO","audit which client accessed which tools and when","revoke access instantly by disabling API keys or revoking OAuth tokens"],"best_for":["enterprises with multi-tenant requirements and strict access control","teams using corporate SSO and needing to map identities to tool access","organizations requiring audit trails for compliance (SOC2, HIPAA)"],"limitations":["API key scoping is coarse-grained at namespace/tool level — no row-level or parameter-level access control","OAuth token validation requires network calls to external provider on each request (unless caching is enabled)","multi-tenancy is logical isolation only — no cryptographic separation of data per tenant"],"requires":["PostgreSQL for API key storage","OAuth provider configuration (client ID, secret, discovery endpoint) for OAuth flows","HTTP server with session middleware for OAuth callback handling"],"input_types":["API key (bearer token in Authorization header)","OAuth authorization code or refresh token","endpoint and tool access scope definitions"],"output_types":["authenticated session with scoped access claims","audit log entries with client identity, timestamp, endpoint, tool invoked"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_4","uri":"capability://data.processing.analysis.tool.discovery.and.synchronization.with.persistent.registry","name":"tool discovery and synchronization with persistent registry","description":"Automatically discovers tools from connected MCP servers via the MCP list_tools protocol, persists tool definitions in PostgreSQL, and maintains a synchronized registry that updates when upstream servers change. Discovery runs on-demand or on a schedule, comparing upstream tool lists against the persisted registry to detect additions, removals, and schema changes. Tool metadata (name, description, input schema, output schema) is stored with namespace-specific overrides applied at query time, enabling tool customization without modifying the canonical definition.","intents":["automatically detect new tools added to upstream MCP servers without manual configuration","maintain a searchable registry of all available tools across all namespaces","track tool schema changes and alert administrators to breaking changes","apply namespace-specific tool overrides (rename, hide, modify schema) without duplicating tool definitions"],"best_for":["teams managing many MCP servers and wanting automated tool inventory","organizations needing to track tool availability and schema changes over time","builders wanting to apply namespace-specific customizations without forking servers"],"limitations":["discovery is eventually consistent — newly added tools may have propagation delay (seconds to minutes depending on schedule)","tool schema changes are detected but not automatically migrated — clients using old schemas may break","discovery requires MCP servers to be reachable and responsive — unreachable servers are marked as failed but don't block other discoveries"],"requires":["PostgreSQL for tool registry persistence","MCP servers with list_tools support","periodic job scheduler (cron or background task) for scheduled discovery"],"input_types":["MCP server configuration (endpoint, credentials)","discovery trigger (on-demand API call or scheduled job)"],"output_types":["tool registry with canonical definitions (name, description, input/output schema)","namespace-specific tool overrides (renamed tools, filtered tools, schema modifications)","discovery audit log with timestamp, server, tools added/removed/modified"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_5","uri":"capability://automation.workflow.session.pool.management.with.cold.start.optimization","name":"session pool management with cold-start optimization","description":"Pre-allocates and maintains a pool of persistent connections to each MCP server, eliminating per-request connection overhead and cold-start latency. The session pool manager maintains a configurable pool size per server, reuses connections across multiple client requests, and implements connection health checks with automatic reconnection on failure. Sessions are borrowed from the pool on client request and returned after tool invocation completes, with idle timeout and maximum lifetime policies to prevent resource leaks.","intents":["reduce latency for tool invocations by reusing pre-established MCP server connections","handle multiple concurrent clients without exhausting server connection limits","automatically recover from transient server failures via health checks and reconnection","monitor pool utilization and connection health for operational visibility"],"best_for":["high-throughput deployments where connection overhead is significant (100+ requests/sec)","teams with strict latency requirements (sub-100ms tool invocation)","operators needing visibility into connection pool health and utilization"],"limitations":["pre-allocated pools consume memory and connections even when idle — pool size must be tuned per deployment","connection reuse assumes MCP servers are stateless — stateful servers may have issues with connection pooling","health checks add periodic overhead — misconfigured checks can cause unnecessary reconnections"],"requires":["MCP servers that support persistent connections (stdio, HTTP, SSE)","memory budget for pre-allocated connections (typically 1-10MB per connection)","configuration of pool size, idle timeout, and health check interval"],"input_types":["pool configuration (min/max pool size, idle timeout, health check interval)","MCP server endpoint configuration"],"output_types":["borrowed session object with MCP client interface","pool metrics (active connections, idle connections, wait time, reconnection count)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_6","uri":"capability://automation.workflow.configuration.management.with.declarative.namespace.and.endpoint.definitions","name":"configuration management with declarative namespace and endpoint definitions","description":"Provides a declarative configuration system for defining MCP servers, namespaces, and endpoints via a Next.js UI and tRPC backend, with all configurations persisted in PostgreSQL via Drizzle ORM. Administrators define which MCP servers to connect to, which tools to aggregate into which namespaces, and which endpoints to expose publicly. Configuration changes are applied dynamically without requiring server restart, with validation and conflict detection to prevent invalid configurations.","intents":["define and manage MCP server connections without editing config files or restarting","create and modify namespaces to organize tools by team, project, or capability","expose endpoints with different authentication schemes and tool subsets","validate configurations before applying to catch errors early"],"best_for":["teams wanting a UI-driven approach to MCP server management","organizations needing to modify configurations frequently without downtime","operators preferring declarative configuration over imperative setup"],"limitations":["UI is web-based only — no CLI or IaC (Infrastructure as Code) support for GitOps workflows","configuration changes are applied immediately without staging/approval workflow","no version control or rollback mechanism for configuration changes"],"requires":["PostgreSQL database for configuration storage","Next.js frontend for UI","tRPC backend for type-safe configuration mutations"],"input_types":["MCP server configuration (name, endpoint, transport, credentials)","namespace definitions (name, description, tool filters)","endpoint definitions (name, namespace, protocol, authentication)"],"output_types":["persisted configuration in PostgreSQL","validation errors or success confirmation","applied configuration state (active servers, namespaces, endpoints)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_7","uri":"capability://tool.use.integration.mcp.inspector.interface.for.tool.testing.and.debugging","name":"mcp inspector interface for tool testing and debugging","description":"Provides a web-based inspector UI for testing tool invocations, viewing tool schemas, and debugging MCP server behavior. The inspector allows administrators to select a tool from any namespace, construct input parameters via a form or JSON editor, invoke the tool, and view the response. Request/response history is maintained for debugging, with detailed error messages and server logs visible in the UI.","intents":["test tool invocations without writing client code","debug tool schema issues or unexpected behavior","verify that tool customizations (overrides, filters) are applied correctly","inspect MCP server responses and error messages"],"best_for":["administrators setting up and validating MCP server configurations","developers debugging tool integration issues","teams wanting to test tools before exposing them to clients"],"limitations":["inspector is UI-only — no programmatic API for automated testing","request history is in-memory only — not persisted across restarts","inspector has no rate limiting — can be used to DOS upstream servers if misconfigured"],"requires":["web browser access to MetaMCP UI","authentication to access inspector (depends on endpoint auth scheme)"],"input_types":["tool selection (namespace + tool name)","tool parameters (form fields or JSON)"],"output_types":["tool response (JSON or structured data)","error messages and stack traces","request/response history"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-metatool-ai--metamcp__cap_8","uri":"capability://tool.use.integration.tool.override.and.customization.system.with.namespace.specific.modifications","name":"tool override and customization system with namespace-specific modifications","description":"Enables namespace-specific tool customization via a declarative override system that modifies tool names, descriptions, input/output schemas, and visibility without forking upstream servers. 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The Docker image includes the Next.js frontend, Node.js backend, and all configuration management logic. Environment variables control database connection, authentication providers, and MCP server endpoints, enabling configuration without rebuilding the image.","intents":["deploy MetaMCP to any Docker-compatible infrastructure (Kubernetes, Docker Compose, VMs)","self-host MetaMCP without relying on cloud services","integrate MetaMCP into existing Docker-based deployment pipelines","scale MetaMCP horizontally by running multiple container instances"],"best_for":["teams with existing Docker/Kubernetes infrastructure","organizations with data residency or compliance requirements preventing cloud deployment","operators wanting full control over deployment and scaling"],"limitations":["Docker image size is large (~500MB) due to Node.js and dependencies — slow to pull on bandwidth-constrained networks","horizontal scaling requires external PostgreSQL and session store — single-instance deployments are not horizontally scalable","Docker networking requires careful configuration for MCP server connectivity — servers must be reachable from container network"],"requires":["Docker runtime (Docker Desktop, Docker Engine, or container orchestration platform)","PostgreSQL database (external or containerized)","network connectivity from container to MCP servers","environment variables for configuration (DATABASE_URL, OAUTH_CLIENT_ID, etc.)"],"input_types":["Docker image (from registry or built locally)","environment variables for configuration","volume mounts for persistent data (optional)"],"output_types":["running MetaMCP container with exposed ports (3000 for UI, 8000 for API)","logs streamed to stdout/stderr"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":44,"verified":false,"data_access_risk":"high","permissions":["PostgreSQL database for configuration persistence","Docker runtime for containerized deployment","2+ MCP servers accessible via stdio, SSE, or HTTP transports","Node.js 18+ for backend runtime","namespace configuration with middleware definitions","TypeScript for custom middleware development","Docker rebuild for custom middleware deployment","multiple MetaMCP instances deployed and accessible","tool naming conventions that enable disambiguation (e.g., namespace:tool_name)","health check configuration (interval, timeout, failure threshold)"],"failure_modes":["session pool pre-allocation requires upfront memory/connection overhead proportional to pool size","tool discovery synchronization is eventually consistent — newly added tools on upstream servers may have propagation delay","namespace isolation is logical, not cryptographic — relies on authentication layer for true security boundaries","middleware execution adds latency per pipeline stage — complex pipelines may add 50-200ms per invocation","custom middleware requires TypeScript knowledge and recompilation/redeployment","middleware state is not persisted — stateful transformations require external storage","nested MetaMCP adds latency due to additional hops — each level adds request/response overhead","tool name disambiguation requires careful naming conventions — ambiguous names can cause routing errors","debugging nested MetaMCP chains is complex — errors may originate from any level in the chain","automatic reconnection may mask underlying server issues — operators must monitor reconnection frequency","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.5206161704741397,"quality":0.35,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.062Z","last_scraped_at":"2026-05-03T13:56:59.049Z","last_commit":"2026-02-08T03:43:11Z"},"community":{"stars":2280,"forks":334,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=metatool-ai--metamcp","compare_url":"https://unfragile.ai/compare?artifact=metatool-ai--metamcp"}},"signature":"uyjcpB9TLkj5pw9qJhsx5+UPkNcxBcsTyYHD77hs8BQYOwH4Xb1JUlEbMExxsvOjQ+ODHVp9w6TjfJTM9NpqDw==","signedAt":"2026-06-21T01:48:49.463Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/metatool-ai--metamcp","artifact":"https://unfragile.ai/metatool-ai--metamcp","verify":"https://unfragile.ai/api/v1/verify?slug=metatool-ai--metamcp","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"}}