{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-teamcity","slug":"teamcity","name":"TeamCity","type":"mcp","url":"https://github.com/itcaat/teamcity-mcp","page_url":"https://unfragile.ai/teamcity","categories":["mcp-servers","app-builders"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-teamcity__cap_0","uri":"capability://tool.use.integration.mcp.protocol.translation.to.teamcity.rest.api","name":"mcp protocol translation to teamcity rest api","description":"Translates incoming Model Context Protocol (MCP) JSON-RPC 2.0 requests into TeamCity REST API calls through a dedicated protocol handler (internal/mcp/handler.go) that manages session lifecycle, request routing, and response marshaling. The handler implements the full MCP specification including initialization, resource discovery, and tool invocation, converting structured MCP messages into authenticated HTTP requests to TeamCity's /app/rest endpoints.","intents":["Enable AI agents to interact with TeamCity using standardized MCP protocol instead of raw REST API","Translate natural language requests from Claude/Cursor into TeamCity operations","Maintain MCP session state and handle protocol-level concerns transparently"],"best_for":["AI-powered development tools (Claude Desktop, Cursor) that support MCP","Teams building custom LLM agents that need TeamCity integration","Organizations standardizing on MCP for CI/CD tool access"],"limitations":["Requires MCP-compatible client (Claude Desktop, Cursor, or custom MCP consumer)","Protocol overhead adds latency compared to direct REST API calls","MCP specification version compatibility must be maintained across updates"],"requires":["TeamCity server 2020.1+ with REST API enabled","MCP-compatible client application","Valid TeamCity authentication credentials (token or username/password)"],"input_types":["JSON-RPC 2.0 requests","MCP resource URIs (teamcity://projects, teamcity://builds, etc.)","Tool invocation payloads with structured parameters"],"output_types":["JSON-RPC 2.0 responses","MCP resource representations","Tool execution results with status and data"],"categories":["tool-use-integration","protocol-translation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_1","uri":"capability://automation.workflow.multi.transport.server.with.http.websocket.and.stdio.support","name":"multi-transport server with http, websocket, and stdio support","description":"Implements a production-grade server (internal/server/server.go) supporting three distinct transport mechanisms: HTTP for REST-like access, WebSocket for persistent bidirectional communication, and STDIO for local process integration. The server component handles connection lifecycle management, request routing, and graceful shutdown across all transports, allowing flexible deployment in cloud, desktop, and local development environments.","intents":["Deploy TeamCity MCP server in cloud environments via HTTP/WebSocket","Integrate with local AI tools (Claude Desktop, Cursor) via STDIO transport","Support multiple client connection patterns without code duplication"],"best_for":["Teams deploying MCP servers in containerized/cloud infrastructure","Desktop application developers integrating with Claude Desktop or Cursor","Organizations needing flexible transport options for different deployment scenarios"],"limitations":["STDIO transport limited to single client connection per process instance","WebSocket connections require persistent network availability","HTTP transport lacks built-in request authentication (relies on TeamCity credentials only)"],"requires":["Go runtime (server is written in Go)","Network access to TeamCity server for all transports","For STDIO: local process spawning capability in client application"],"input_types":["HTTP POST requests with JSON bodies","WebSocket frames with JSON-RPC payloads","STDIO streams with newline-delimited JSON"],"output_types":["HTTP responses with JSON bodies","WebSocket frames with JSON-RPC responses","STDIO streams with newline-delimited JSON"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_10","uri":"capability://automation.workflow.response.caching.and.health.check.monitoring","name":"response caching and health check monitoring","description":"Implements caching layer for frequently accessed TeamCity data (projects, build types, agents) and periodic health checks to monitor TeamCity server availability. The caching system reduces API calls to TeamCity and improves response latency for resource discovery operations. Health checks detect connectivity issues and enable graceful degradation or alerting when TeamCity becomes unavailable.","intents":["Reduce latency for repeated resource discovery queries","Monitor TeamCity server health and availability","Detect and alert on connectivity issues","Improve overall system resilience"],"best_for":["High-traffic MCP server deployments with frequent resource queries","Production environments requiring availability monitoring","Teams needing visibility into TeamCity connectivity status"],"limitations":["Cache TTL is fixed; no dynamic cache invalidation","Stale cache may be served if TeamCity is temporarily unavailable","Health checks add periodic load to TeamCity server","No cache warming or preloading strategy"],"requires":["Configuration of cache TTL values","Health check interval settings","Monitoring/alerting system to consume health check results"],"input_types":["Resource queries (projects, build types, agents)","Health check interval configuration"],"output_types":["Cached resource data (if available)","Health status (healthy/unhealthy)","Latency metrics"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_11","uri":"capability://tool.use.integration.json.rpc.2.0.protocol.compliance.and.error.handling","name":"json-rpc 2.0 protocol compliance and error handling","description":"Implements full JSON-RPC 2.0 specification compliance in the MCP protocol handler, including proper request/response formatting, error code mapping, and exception handling. The handler validates incoming requests, maps TeamCity API errors to JSON-RPC error codes, and returns properly formatted error responses with descriptive messages. This ensures compatibility with standard JSON-RPC clients and enables clear error communication to AI agents.","intents":["Ensure compatibility with standard JSON-RPC 2.0 clients","Provide clear error messages for failed operations","Enable proper error handling in AI agent workflows","Support request validation and parameter checking"],"best_for":["Developers building custom MCP clients","Teams requiring strict JSON-RPC 2.0 compliance","Automation workflows that need reliable error handling"],"limitations":["Error messages are limited to JSON-RPC standard error codes","No custom error types or structured error details","Request validation is basic; complex parameter validation delegated to TeamCity","Batch request processing may not be fully supported"],"requires":["JSON-RPC 2.0 compatible client","Understanding of JSON-RPC error codes and response format"],"input_types":["JSON-RPC 2.0 request objects","Method names and parameters"],"output_types":["JSON-RPC 2.0 response objects","Error responses with error code and message"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_2","uri":"capability://search.retrieval.teamcity.resource.discovery.and.listing.via.mcp.resources","name":"teamcity resource discovery and listing via mcp resources","description":"Exposes TeamCity resources (projects, build types, builds, agents) as MCP resource URIs (teamcity://projects, teamcity://buildTypes, teamcity://builds, teamcity://agents) that map directly to TeamCity REST API endpoints (/app/rest/projects, /app/rest/buildTypes, etc.). The resource handler fetches and structures data from TeamCity, enabling AI agents to discover and enumerate CI/CD infrastructure without needing to understand TeamCity's API structure.","intents":["List all TeamCity projects and their configurations","Enumerate available build types and their parameters","Discover running and historical builds with filtering","View available build agents and their status"],"best_for":["AI agents needing to understand TeamCity project structure","Users asking natural language questions about CI/CD infrastructure","Automation workflows that need to discover build configurations dynamically"],"limitations":["Resource listing returns full dataset without built-in pagination (large TeamCity instances may return large payloads)","No filtering at resource level — filtering must happen in client or via search tools","Resource freshness depends on TeamCity API response time (no client-side caching of resource lists)"],"requires":["TeamCity REST API access with appropriate permissions","Valid authentication token or credentials","Network connectivity to TeamCity server"],"input_types":["MCP resource URI requests (teamcity://projects, etc.)"],"output_types":["JSON-structured resource representations","Lists of project/build/agent objects with metadata"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_3","uri":"capability://automation.workflow.build.triggering.with.branch.and.property.parameters","name":"build triggering with branch and property parameters","description":"Implements the trigger_build tool that initiates new TeamCity builds with support for specifying target branch, custom build parameters, and build type selection. The tool accepts buildTypeId, branchName, and properties parameters, constructs a TeamCity build request, and returns build ID and status. This enables AI agents to programmatically start CI/CD pipelines with context-specific configuration.","intents":["Trigger builds on specific branches from natural language requests","Start builds with custom parameters (environment variables, feature flags, etc.)","Initiate builds for specific build configurations by name or ID"],"best_for":["Developers asking AI to 'run the build on this branch'","Automation workflows that need to trigger builds with dynamic parameters","Teams using AI agents to manage CI/CD pipeline execution"],"limitations":["Requires explicit buildTypeId — no fuzzy matching or name-based lookup","Parameters must be pre-defined in TeamCity build configuration","No support for queuing priority or agent selection","Synchronous operation returns immediately; does not wait for build completion"],"requires":["TeamCity user with 'Trigger builds' permission","Valid buildTypeId from TeamCity configuration","Knowledge of available build parameters for the target build type"],"input_types":["buildTypeId (string, required)","branchName (string, optional)","properties (object with key-value pairs, optional)"],"output_types":["Build ID (string)","Build status (queued/running)","Build URL or reference"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_4","uri":"capability://automation.workflow.build.cancellation.with.comment.annotation","name":"build cancellation with comment annotation","description":"Implements the cancel_build tool that stops running TeamCity builds by buildId with optional comment annotation. The tool sends a cancellation request to TeamCity's build management API, allowing AI agents to halt in-progress builds and provide context about why the cancellation occurred. Comments are stored in TeamCity's build history for audit and debugging purposes.","intents":["Stop failing or stuck builds from natural language requests","Cancel builds with explanatory comments for team visibility","Implement automated build cleanup workflows"],"best_for":["Developers asking AI to 'stop this build'","Automated workflows that need to halt builds based on conditions","Teams managing build queues and resource allocation"],"limitations":["Can only cancel running builds; cannot cancel queued builds in some TeamCity versions","Requires explicit buildId; no pattern matching or bulk cancellation","Comments are optional but provide no structured metadata","No rollback capability for builds that have already completed"],"requires":["TeamCity user with 'Cancel builds' permission","Valid buildId of a running build","Network connectivity to TeamCity server"],"input_types":["buildId (string, required)","comment (string, optional)"],"output_types":["Cancellation status (success/failure)","Build state after cancellation"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_5","uri":"capability://automation.workflow.build.pinning.to.prevent.automatic.cleanup","name":"build pinning to prevent automatic cleanup","description":"Implements the pin_build tool that marks TeamCity builds as 'pinned' to prevent automatic cleanup and retention policy deletion. The tool accepts buildId, pin (boolean), and optional comment parameters, allowing AI agents to preserve important builds (successful releases, baseline builds) from garbage collection. Pinned builds remain accessible for artifact retrieval and historical analysis.","intents":["Preserve important builds from automatic cleanup","Mark release or baseline builds for long-term retention","Annotate pinned builds with context about why they were preserved"],"best_for":["Release management workflows that need to preserve production builds","Teams using AI to manage build artifact retention","Automated processes that identify and pin important builds"],"limitations":["Pinning is binary (pinned/unpinned); no granular retention policies","Pinned builds still consume disk space; no automatic archival","No bulk pinning operation; must pin builds individually","Comments on pinned builds are optional and unstructured"],"requires":["TeamCity user with 'Pin/unpin builds' permission","Valid buildId","Understanding of TeamCity retention policies"],"input_types":["buildId (string, required)","pin (boolean, required — true to pin, false to unpin)","comment (string, optional)"],"output_types":["Pin status (pinned/unpinned)","Build reference with updated metadata"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_6","uri":"capability://automation.workflow.build.tagging.with.add.remove.operations","name":"build tagging with add/remove operations","description":"Implements the set_build_tag tool that manages TeamCity build tags through add and remove operations. The tool accepts buildId, tags (array of tag strings to add), and removeTags (array of tag strings to remove) parameters, allowing AI agents to organize and categorize builds with semantic labels. Tags enable filtering, searching, and organizing builds by release version, environment, or custom metadata.","intents":["Tag builds with release versions or environment labels","Organize builds by custom categories (e.g., 'production-ready', 'hotfix')","Remove outdated tags from builds during cleanup workflows"],"best_for":["Release management workflows that need to label builds","Teams using AI to organize and categorize CI/CD artifacts","Automated processes that apply semantic tags based on build results"],"limitations":["Tags are free-form strings; no validation or predefined tag schemas","No bulk tagging operation; must tag builds individually","Tags are not queryable through search_builds tool (separate concern)","Tag removal is explicit; no wildcard or pattern-based removal"],"requires":["TeamCity user with 'Tag builds' permission","Valid buildId","Pre-agreed tag naming conventions within team"],"input_types":["buildId (string, required)","tags (array of strings, optional — tags to add)","removeTags (array of strings, optional — tags to remove)"],"output_types":["Updated build tags (array of strings)","Build reference with new tag metadata"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_7","uri":"capability://search.retrieval.build.artifact.download.and.retrieval","name":"build artifact download and retrieval","description":"Implements the download_artifact tool that retrieves build artifacts from TeamCity by buildId and artifactPath. The tool constructs artifact download URLs, handles authentication, and streams artifact content to the client. This enables AI agents to access build outputs (binaries, logs, reports) for analysis, deployment, or distribution without requiring direct TeamCity UI access.","intents":["Download build artifacts for deployment or analysis","Retrieve logs or reports from completed builds","Access build outputs programmatically from AI workflows"],"best_for":["Deployment automation workflows that need to fetch build artifacts","AI agents analyzing build outputs or logs","Teams automating artifact distribution and deployment"],"limitations":["Requires exact artifactPath; no wildcard or pattern matching","Large artifacts may timeout or exceed memory limits","No streaming support for very large files (depends on implementation)","Artifact paths must be known in advance; no artifact discovery tool"],"requires":["TeamCity user with 'View build artifacts' permission","Valid buildId and exact artifactPath","Sufficient storage/memory for artifact content"],"input_types":["buildId (string, required)","artifactPath (string, required — path within build artifacts)"],"output_types":["Binary artifact content (file bytes)","Text artifact content (logs, reports)","HTTP redirect to artifact URL (implementation-dependent)"],"categories":["search-retrieval","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_8","uri":"capability://search.retrieval.advanced.build.search.with.multi.criteria.filtering","name":"advanced build search with multi-criteria filtering","description":"Implements the search_builds tool that queries TeamCity builds using multiple filter criteria: status (success/failure/running), branch, user (who triggered the build), and tags. The tool constructs TeamCity REST API search queries with combined filters, returning matching builds with metadata. This enables AI agents to find specific builds based on complex criteria without enumerating all builds.","intents":["Find failed builds on a specific branch for debugging","Locate builds triggered by a specific user","Search for builds with specific tags (e.g., 'production-ready')","Discover recent builds matching multiple criteria"],"best_for":["Developers searching for specific builds in large TeamCity instances","Automation workflows that need to find builds matching criteria","AI agents analyzing build history and patterns"],"limitations":["Search filters are AND-combined; no OR logic or complex boolean queries","Tag search may not be supported depending on TeamCity version","Results are limited by TeamCity API pagination (default limit ~100 builds)","Search is case-sensitive for string criteria"],"requires":["TeamCity REST API with search capability","Valid filter parameters (status, branch, user, tags)","Understanding of TeamCity build status values"],"input_types":["status (string, optional — 'success', 'failure', 'running')","branch (string, optional — branch name)","user (string, optional — username who triggered build)","tags (array of strings, optional — build tags)"],"output_types":["Array of matching build objects","Build metadata (ID, status, branch, timestamp, tags)"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-teamcity__cap_9","uri":"capability://automation.workflow.configuration.management.with.environment.variables.and.secrets","name":"configuration management with environment variables and secrets","description":"Manages server configuration through environment variables and configuration files (internal/config/config.go), including TeamCity server URL, authentication credentials, transport settings, and logging configuration. The configuration system supports multiple authentication methods (token-based, username/password) and transport modes (HTTP, WebSocket, STDIO), allowing flexible deployment across different environments without code changes.","intents":["Configure TeamCity server connection details for different environments","Manage authentication credentials securely via environment variables","Select transport mode (HTTP, WebSocket, STDIO) based on deployment context","Control logging verbosity and output format"],"best_for":["DevOps teams deploying MCP server in cloud/container environments","Developers configuring local development instances","Organizations managing multiple TeamCity instances with different credentials"],"limitations":["Configuration is static at startup; no hot-reload capability","Secrets must be provided via environment variables (no encrypted config files)","No configuration validation at startup (errors may occur at runtime)","Limited configuration options compared to TeamCity's full API"],"requires":["Environment variables set before server startup","Valid TeamCity server URL and authentication credentials","Understanding of MCP transport modes"],"input_types":["Environment variables (TEAMCITY_URL, TEAMCITY_TOKEN, etc.)","Configuration file (YAML/JSON format, optional)"],"output_types":["Parsed configuration object","Server startup with configured settings"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":32,"verified":false,"data_access_risk":"high","permissions":["TeamCity server 2020.1+ with REST API enabled","MCP-compatible client application","Valid TeamCity authentication credentials (token or username/password)","Go runtime (server is written in Go)","Network access to TeamCity server for all transports","For STDIO: local process spawning capability in client application","Configuration of cache TTL values","Health check interval settings","Monitoring/alerting system to consume health check results","JSON-RPC 2.0 compatible client"],"failure_modes":["Requires MCP-compatible client (Claude Desktop, Cursor, or custom MCP consumer)","Protocol overhead adds latency compared to direct REST API calls","MCP specification version compatibility must be maintained across updates","STDIO transport limited to single client connection per process instance","WebSocket connections require persistent network availability","HTTP transport lacks built-in request authentication (relies on TeamCity credentials only)","Cache TTL is fixed; no dynamic cache invalidation","Stale cache may be served if TeamCity is temporarily unavailable","Health checks add periodic load to TeamCity server","No cache warming or preloading strategy","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.34,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.9,"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":"2026-05-24T12:16:21.012Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=teamcity","compare_url":"https://unfragile.ai/compare?artifact=teamcity"}},"signature":"bli/lfcbt/gqHOV1w2cVD38NsvIQahteLa86bU+lg5M70RXm0geK2ZJ2XU5Vtjodk5xGFprZpT+TiPnyj4qZBQ==","signedAt":"2026-06-15T15:37:26.639Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/teamcity","artifact":"https://unfragile.ai/teamcity","verify":"https://unfragile.ai/api/v1/verify?slug=teamcity","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"}}