{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github_mcp-jamubc-gemini-mcp-tool","slug":"mcp-jamubc-gemini-mcp-tool","name":"gemini-mcp-tool","type":"mcp","url":"https://github.com/jamubc/gemini-mcp-tool","page_url":"https://unfragile.ai/mcp-jamubc-gemini-mcp-tool","categories":["mcp-servers"],"tags":["ai","claude","cli","codebase-analysis","file-analysis","gemini","mcp","model-context-protocol","npm","typescript"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_0","uri":"capability://tool.use.integration.mcp.protocol.bridging.to.gemini.cli.with.request.translation","name":"mcp protocol bridging to gemini cli with request translation","description":"Implements a three-layer bridge pattern that translates incoming MCP protocol requests into Gemini CLI commands and marshals responses back through the MCP SDK. The server uses @modelcontextprotocol/sdk to handle MCP protocol handshakes, tool registration, and message routing, then spawns Gemini CLI processes as child processes to execute analysis tasks. This architecture decouples the MCP client (Claude Desktop) from direct Gemini CLI dependency, enabling seamless integration without modifying either system.","intents":["Enable Claude Desktop to invoke Gemini's analysis capabilities without leaving the Claude interface","Leverage Gemini's massive context window (2M+ tokens) for large file analysis from within Claude","Route MCP tool calls to Gemini CLI subprocess and stream results back to Claude"],"best_for":["Claude Desktop users who need Gemini's extended context window for codebase analysis","Teams building multi-model AI workflows that require protocol-level interoperability","Developers integrating Gemini capabilities into MCP-compatible AI assistants"],"limitations":["Requires Gemini CLI to be installed and authenticated separately — adds external dependency management overhead","Subprocess spawning for each request adds ~500ms-1s latency per analysis compared to direct API calls","No built-in request queuing or connection pooling — concurrent requests spawn multiple CLI processes, increasing memory overhead","MCP protocol overhead adds ~50-100ms per round-trip for message serialization/deserialization"],"requires":["Node.js 16.0.0 or higher","Google Gemini CLI installed and authenticated with valid API credentials","@modelcontextprotocol/sdk npm package","Claude Desktop or compatible MCP client"],"input_types":["MCP tool call requests (JSON-RPC 2.0 format)","Tool parameters with file paths and prompts","Structured command arguments (@file syntax, model selection)"],"output_types":["MCP tool result responses (JSON-RPC 2.0 format)","Text analysis results from Gemini","Structured error responses with diagnostic information"],"categories":["tool-use-integration","mcp-protocol"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_1","uri":"capability://data.processing.analysis.file.and.directory.reference.resolution.with.syntax","name":"file and directory reference resolution with @ syntax","description":"Implements a file reference system using @ prefix syntax that enables users to pass file and directory paths directly into Gemini analysis prompts. The system parses @-prefixed tokens in user input, resolves them to actual file system paths, reads file contents, and injects them into the Gemini CLI command as context. Supports single files (@src/main.js), directories (@.), and configuration files (@package.json), with automatic path resolution relative to the current working directory. This abstraction allows users to reference files without manually copying/pasting content.","intents":["Analyze specific files or entire directories by referencing them with @ syntax instead of pasting content","Pass multiple file contexts to Gemini in a single analysis request for cross-file understanding","Enable codebase-wide analysis by referencing directory paths that Gemini can process with its large context window"],"best_for":["Developers analyzing large codebases who need to reference multiple files without manual copy-paste","Teams performing codebase audits or refactoring where file context is essential","Users leveraging Gemini's 2M+ token window to analyze entire project structures at once"],"limitations":["No recursive directory traversal filtering — @. includes all files in directory, which may exceed token limits for large projects","No built-in .gitignore or exclusion pattern support — binary files and node_modules are not automatically filtered","File size limits depend on Gemini's token window, not enforced by the tool — very large files may silently truncate","Path resolution is relative to CWD only — no support for absolute paths or environment variable expansion"],"requires":["File system read permissions for referenced paths","Current working directory set to project root or parent of referenced files","Gemini CLI with sufficient context window to accommodate file contents"],"input_types":["Text prompts with embedded @file or @directory references","File paths (relative or absolute)","Directory paths for bulk analysis"],"output_types":["Resolved file contents injected into Gemini prompts","Analysis results from Gemini with file context applied"],"categories":["data-processing-analysis","file-handling"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_10","uri":"capability://automation.workflow.subprocess.lifecycle.management.with.process.spawning.and.cleanup","name":"subprocess lifecycle management with process spawning and cleanup","description":"Manages the lifecycle of Gemini CLI subprocess invocations, including spawning processes with appropriate arguments, capturing stdout/stderr, handling timeouts, and cleaning up resources. The system uses Node.js child_process module to spawn Gemini CLI with the appropriate command and arguments, sets up event handlers for process completion, implements timeout logic to prevent hung processes, and ensures resources are cleaned up even if requests fail. This abstraction isolates the MCP layer from subprocess management complexity.","intents":["Invoke Gemini CLI commands reliably without manual process management","Prevent hung processes from blocking subsequent requests by implementing timeouts","Capture and format Gemini CLI output for return to MCP client"],"best_for":["MCP server implementations that need to invoke external CLI tools","Teams building subprocess-based integrations who want reference patterns","Developers who need reliable process lifecycle management without external libraries"],"limitations":["Subprocess spawning adds ~500ms-1s overhead per request compared to direct API calls","No process pooling or reuse — each request spawns a new process, increasing resource overhead","Timeout handling is process-level only — no per-operation timeouts within a single Gemini CLI invocation","Signal handling may be OS-specific — process cleanup behavior may differ between Linux, macOS, and Windows","No built-in retry logic — failed processes are not automatically retried"],"requires":["Node.js 16.0.0+ with child_process module","Gemini CLI executable in PATH or specified as absolute path","Sufficient system resources to spawn processes (memory, file descriptors)"],"input_types":["Gemini CLI command name (analyze, sandbox, etc.)","Command arguments (model, prompt, file paths)","Timeout duration in milliseconds"],"output_types":["Process stdout captured as string or stream","Process stderr for error diagnostics","Exit code indicating success/failure"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_11","uri":"capability://code.generation.editing.typescript.type.safety.with.zod.schema.validation","name":"typescript type safety with zod schema validation","description":"Uses TypeScript and Zod for end-to-end type safety across the MCP request-response pipeline. Tool parameters are defined as Zod schemas that validate incoming requests at the MCP layer, ensuring type correctness before passing data to Gemini CLI. TypeScript provides compile-time type checking for internal functions and data structures, while Zod provides runtime validation for untrusted input from MCP clients. This dual-layer approach prevents type-related bugs and provides clear error messages when validation fails.","intents":["Catch parameter type errors at validation time rather than at Gemini CLI invocation","Provide clear error messages when MCP clients send invalid parameters","Enable IDE autocomplete and type hints for developers extending the tool"],"best_for":["Teams building production MCP servers who need robust input validation","Developers who prefer type-safe languages and want compile-time guarantees","Projects where parameter validation errors need to be caught early and reported clearly"],"limitations":["Zod validation adds ~5-10ms overhead per request for schema checking","TypeScript compilation step adds build complexity compared to plain JavaScript","Zod schemas must be maintained in sync with Gemini CLI parameter requirements — schema drift can cause validation failures","Type safety is only as good as the schema definitions — incomplete or incorrect schemas provide false confidence"],"requires":["TypeScript 4.5+ for type definitions","Zod 3.0+ for runtime schema validation","TypeScript compiler (tsc) or tsx for execution"],"input_types":["MCP tool invocation parameters","Zod schema definitions for validation"],"output_types":["Validated parameters passed to Gemini CLI","Zod validation errors with detailed error messages","Type-safe internal function signatures"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_2","uri":"capability://code.generation.editing.sandbox.isolated.code.execution.via.gemini.sandbox.mode","name":"sandbox-isolated code execution via gemini sandbox mode","description":"Provides a safe code execution environment by delegating execution to Gemini's built-in sandbox capabilities rather than running code locally. When users invoke the sandbox-test tool with code snippets, the system passes the code to Gemini CLI with sandbox mode enabled, which executes the code in an isolated environment and returns execution results (stdout, stderr, exit codes). This approach avoids local process spawning security risks and leverages Gemini's managed sandbox infrastructure for resource isolation and timeout enforcement.","intents":["Test code snippets safely without executing them locally on the developer's machine","Validate code behavior before committing or deploying by running it in Gemini's sandbox","Get execution results and error messages from code analysis without local process management overhead"],"best_for":["Developers testing untrusted or experimental code snippets","Teams with security policies prohibiting local code execution in development workflows","Users who want execution results without managing local runtime environments (Python, Node.js, etc.)"],"limitations":["Sandbox execution latency is 2-5 seconds per request due to Gemini API round-trip and sandbox initialization","No persistent state between sandbox executions — each invocation is isolated, preventing multi-step debugging workflows","Sandbox environment is read-only for file system — code cannot write files or modify local state","Language support depends on Gemini's sandbox capabilities, which may not include all runtime versions or exotic languages","Network access from sandbox is restricted or disabled — code cannot make external API calls or fetch remote resources"],"requires":["Gemini CLI with sandbox mode enabled","Valid Gemini API credentials with sandbox execution permissions","Code snippet in a language supported by Gemini's sandbox (Python, JavaScript, etc.)"],"input_types":["Code snippets (Python, JavaScript, etc.)","Execution parameters (timeout, environment variables)","Standard input for code execution"],"output_types":["Execution results (stdout, stderr)","Exit codes and error messages","Execution metadata (duration, resource usage)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_3","uri":"capability://tool.use.integration.multi.model.selection.with.gemini.model.routing","name":"multi-model selection with gemini model routing","description":"Enables users to select between multiple Gemini models (gemini-2.5-flash, gemini-pro, gemini-nano) for different analysis tasks, with the system routing requests to the specified model via Gemini CLI. The tool accepts a model parameter that is passed directly to the Gemini CLI invocation, allowing users to trade off between speed (flash), capability (pro), and cost/latency (nano). Model selection is transparent to the MCP layer — the system simply forwards the model parameter to the CLI and returns results from the selected model.","intents":["Use faster, cheaper models (gemini-nano, gemini-2.5-flash) for simple analysis tasks to reduce latency and cost","Switch to more capable models (gemini-pro) for complex reasoning or multi-step analysis when accuracy is critical","Optimize model selection per-request based on task complexity without changing tool configuration"],"best_for":["Cost-conscious teams analyzing large volumes of files who want to use cheaper models for simple tasks","Developers optimizing latency who need fast responses for interactive analysis workflows","Teams with heterogeneous analysis needs requiring different model capabilities for different file types"],"limitations":["Model availability depends on Gemini API quotas and regional availability — not all models may be accessible in all regions","No automatic model selection based on task complexity — users must manually choose the appropriate model","Model performance characteristics (latency, accuracy, cost) are not exposed by the tool — users must know model trade-offs externally","No fallback mechanism if selected model is unavailable — requests fail rather than gracefully degrading to alternative models"],"requires":["Gemini API credentials with access to selected models","Gemini CLI version supporting the specified model","Model name matching Gemini's official model identifiers (gemini-2.5-flash, gemini-pro, gemini-nano)"],"input_types":["Model name as string parameter","Analysis prompt and file references","Model-specific configuration options"],"output_types":["Analysis results from selected model","Model metadata (name, version used)","Results formatted consistently across models"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_4","uri":"capability://text.generation.language.dual.interface.support.natural.language.commands.and.slash.commands","name":"dual interface support: natural language commands and slash commands","description":"Provides two interaction modes for users: natural language commands (e.g., 'ask gemini to analyze @file') and structured slash commands (e.g., '/analyze prompt:@file', '/sandbox prompt:code'). The system parses incoming requests to detect slash command syntax, extracts parameters, and routes them to the appropriate tool handler. Natural language commands are passed directly to Gemini for interpretation. This dual interface accommodates both conversational and structured workflows without requiring users to switch tools.","intents":["Use natural language commands for exploratory analysis when exact parameters are not predetermined","Use slash commands for scripted or repetitive analysis tasks where parameter structure is fixed","Mix both interaction styles in a single workflow without context switching"],"best_for":["Users who prefer conversational interaction for ad-hoc analysis","Teams with scripted analysis workflows that benefit from structured slash command syntax","Developers building automation that needs predictable command parsing"],"limitations":["Natural language command parsing relies on Gemini's interpretation — ambiguous prompts may be misinterpreted","Slash command syntax is not validated before sending to Gemini — malformed commands may produce unclear errors","No command autocomplete or syntax hints in Claude Desktop — users must remember slash command format","Mixing natural language and slash commands in a single message may cause parsing ambiguity"],"requires":["Claude Desktop or MCP client that supports tool invocation","Understanding of slash command syntax for structured workflows","Gemini CLI for natural language command interpretation"],"input_types":["Natural language text (e.g., 'analyze this file')","Slash commands with parameters (e.g., '/analyze prompt:@file')","Mixed natural language and command syntax"],"output_types":["Analysis results from Gemini","Structured responses from slash command handlers","Error messages for malformed commands"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_5","uri":"capability://tool.use.integration.tool.registration.and.capability.advertisement.via.mcp.protocol","name":"tool registration and capability advertisement via mcp protocol","description":"Registers available tools (ask-gemini, sandbox-test, /analyze, /sandbox, /help, /ping) with the MCP server and advertises their capabilities, parameters, and descriptions to the MCP client (Claude Desktop). The system uses the @modelcontextprotocol/sdk to define tool schemas with Zod validation, enabling Claude to understand what parameters each tool accepts and provide autocomplete/validation. Tool registration happens at server startup and is static — tools cannot be dynamically added or removed without restarting the server.","intents":["Enable Claude Desktop to discover available Gemini analysis tools without external documentation","Provide parameter validation and type hints so Claude can construct correct tool invocations","Advertise tool descriptions so Claude can decide which tool to use for a given task"],"best_for":["MCP client developers who need to discover available tools programmatically","Claude Desktop users who benefit from tool autocomplete and parameter hints","Teams building custom MCP servers who need a reference implementation of tool registration"],"limitations":["Tool schemas are static and defined at startup — dynamic tool registration requires server restart","No runtime tool capability negotiation — client must accept all registered tools or none","Tool descriptions are text-only — no rich documentation or examples are embedded in tool schemas","Parameter validation happens at MCP layer only — Gemini CLI may reject parameters that pass MCP validation"],"requires":["@modelcontextprotocol/sdk for tool schema definition","Zod for parameter validation schemas","MCP client that supports tool discovery (Claude Desktop 1.0+)"],"input_types":["Tool schema definitions (name, description, parameters)","Parameter validation rules (Zod schemas)","Tool metadata (category, tags)"],"output_types":["MCP tool list response with full schemas","Tool capability advertisements to MCP client","Parameter validation errors for invalid invocations"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_6","uri":"capability://automation.workflow.streaming.response.handling.for.long.running.analysis","name":"streaming response handling for long-running analysis","description":"Handles streaming responses from Gemini CLI for long-running analysis tasks, allowing results to be streamed back to the MCP client as they become available rather than buffering the entire response. The system captures Gemini CLI stdout in chunks, formats them as MCP response messages, and sends them incrementally to Claude Desktop. This enables users to see partial results while analysis is still running, improving perceived responsiveness for large file analysis or complex reasoning tasks.","intents":["See partial analysis results in real-time while Gemini is still processing large files","Avoid timeout issues by streaming results incrementally instead of waiting for complete response","Improve user experience by showing progress for long-running analysis tasks"],"best_for":["Users analyzing large codebases where analysis takes 10+ seconds","Teams with strict timeout requirements who need to see partial results before timeout","Interactive workflows where users want to see results as they arrive rather than waiting for completion"],"limitations":["Streaming adds complexity to error handling — errors may occur mid-stream after partial results are sent","No built-in progress indicators — users see raw output without context about completion percentage","Streaming may cause results to be fragmented across multiple messages, making it harder to parse structured output","MCP protocol streaming support depends on client implementation — not all MCP clients may handle streaming correctly"],"requires":["MCP client that supports streaming responses (Claude Desktop 1.0+)","Gemini CLI that outputs results to stdout in a streamable format","Node.js stream handling capabilities"],"input_types":["Gemini CLI stdout stream","Analysis requests that produce long-running tasks"],"output_types":["Streamed MCP response messages","Partial analysis results sent incrementally","Final completion message when analysis finishes"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_7","uri":"capability://safety.moderation.error.handling.and.diagnostic.reporting.with.structured.error.responses","name":"error handling and diagnostic reporting with structured error responses","description":"Implements structured error handling that captures failures from Gemini CLI execution, formats them as MCP error responses with diagnostic information, and returns them to the client. When Gemini CLI fails (missing authentication, invalid model, file not found, etc.), the system captures stderr, exit codes, and command context, then formats them as MCP error messages with actionable diagnostic information. This enables users to understand why analysis failed and how to fix it without debugging CLI output directly.","intents":["Understand why Gemini analysis failed (missing auth, invalid model, file not found, etc.)","Get actionable error messages that suggest fixes (e.g., 'Gemini CLI not found — install with npm install -g @google/generative-ai-cli')","Debug integration issues between Claude and Gemini without accessing raw CLI logs"],"best_for":["Users troubleshooting Gemini CLI integration issues","Teams deploying gemini-mcp-tool in production who need clear error diagnostics","Developers building on top of gemini-mcp-tool who need to understand failure modes"],"limitations":["Error messages depend on Gemini CLI's stderr output — unclear CLI errors produce unclear MCP errors","No automatic error recovery — errors are reported but not automatically retried or mitigated","Error context is limited to the failed request — no cross-request error correlation or pattern detection","Sensitive information (API keys, file paths) may be exposed in error messages if not carefully filtered"],"requires":["Gemini CLI that produces meaningful error messages on stderr","MCP client that displays error responses to users"],"input_types":["Gemini CLI stderr output","Exit codes from failed processes","Command context (model, file paths, prompts)"],"output_types":["MCP error responses with error codes","Diagnostic messages explaining failure cause","Suggested remediation steps"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_8","uri":"capability://automation.workflow.connection.health.checking.and.ping.pong.diagnostics","name":"connection health checking and ping/pong diagnostics","description":"Provides a /ping command that tests connectivity between Claude Desktop and the Gemini MCP server, and between the server and Gemini CLI. The ping handler sends a test message through the full request-response pipeline and returns latency metrics and status information. This enables users to verify that the integration is working correctly before attempting analysis, and to diagnose connectivity issues if analysis requests fail.","intents":["Verify that Claude Desktop can communicate with the Gemini MCP server","Test that the MCP server can invoke Gemini CLI successfully","Measure round-trip latency for analysis requests to set expectations"],"best_for":["Users setting up gemini-mcp-tool for the first time who want to verify the integration","Teams troubleshooting connectivity issues between Claude and Gemini","Developers monitoring MCP server health in production"],"limitations":["Ping only tests basic connectivity — it doesn't validate that analysis requests will succeed","Latency measurements from ping may not reflect actual analysis latency due to different payload sizes","No persistent health monitoring — ping is a one-time check, not continuous health tracking","Ping results depend on current system load — latency measurements may vary significantly between runs"],"requires":["MCP client that supports tool invocation (Claude Desktop)","Gemini CLI installed and accessible from the MCP server process"],"input_types":["Optional test message parameter","No other parameters required"],"output_types":["Ping response with status (success/failure)","Round-trip latency in milliseconds","Gemini CLI version information","Server status metadata"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-jamubc-gemini-mcp-tool__cap_9","uri":"capability://text.generation.language.help.command.with.cli.documentation.and.usage.examples","name":"help command with cli documentation and usage examples","description":"Provides a /help command that displays Gemini CLI documentation, available commands, and usage examples directly within Claude Desktop. The system invokes Gemini CLI with the --help flag, captures its output, and returns it formatted as an MCP response. This enables users to learn about Gemini CLI capabilities without leaving Claude or consulting external documentation.","intents":["Learn about Gemini CLI commands and options without leaving Claude Desktop","Discover available Gemini models and their capabilities","Find usage examples for common analysis tasks"],"best_for":["New users learning Gemini CLI capabilities for the first time","Teams onboarding developers to the gemini-mcp-tool workflow","Users who prefer in-tool documentation over external docs"],"limitations":["Help output depends on Gemini CLI version — different versions may have different documentation","Help text is static — it doesn't reflect user's current configuration or available models","No interactive help — users cannot ask follow-up questions about specific commands","Help output may be very long and difficult to navigate in Claude's interface"],"requires":["Gemini CLI installed and accessible","Gemini CLI that supports --help flag"],"input_types":["Optional help topic parameter (e.g., 'analyze', 'sandbox')"],"output_types":["Gemini CLI help text","Available commands and options","Usage examples and syntax"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":47,"verified":false,"data_access_risk":"high","permissions":["Node.js 16.0.0 or higher","Google Gemini CLI installed and authenticated with valid API credentials","@modelcontextprotocol/sdk npm package","Claude Desktop or compatible MCP client","File system read permissions for referenced paths","Current working directory set to project root or parent of referenced files","Gemini CLI with sufficient context window to accommodate file contents","Node.js 16.0.0+ with child_process module","Gemini CLI executable in PATH or specified as absolute path","Sufficient system resources to spawn processes (memory, file descriptors)"],"failure_modes":["Requires Gemini CLI to be installed and authenticated separately — adds external dependency management overhead","Subprocess spawning for each request adds ~500ms-1s latency per analysis compared to direct API calls","No built-in request queuing or connection pooling — concurrent requests spawn multiple CLI processes, increasing memory overhead","MCP protocol overhead adds ~50-100ms per round-trip for message serialization/deserialization","No recursive directory traversal filtering — @. includes all files in directory, which may exceed token limits for large projects","No built-in .gitignore or exclusion pattern support — binary files and node_modules are not automatically filtered","File size limits depend on Gemini's token window, not enforced by the tool — very large files may silently truncate","Path resolution is relative to CWD only — no support for absolute paths or environment variable expansion","Subprocess spawning adds ~500ms-1s overhead per request compared to direct API calls","No process pooling or reuse — each request spawns a new process, increasing resource overhead","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.49926584101306354,"quality":0.49,"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":"2026-05-24T12:16:22.065Z","last_scraped_at":"2026-05-03T14:23:34.856Z","last_commit":"2025-11-25T11:48:56Z"},"community":{"stars":2186,"forks":190,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-jamubc-gemini-mcp-tool","compare_url":"https://unfragile.ai/compare?artifact=mcp-jamubc-gemini-mcp-tool"}},"signature":"67im9rmUy87Zl/G84aYvqGDozBPOmIeU2nUOYckgTiMeFhYOIhTo+F4hakbGC0De3WzYhpIzoW+RUiu3km37Dg==","signedAt":"2026-06-20T09:39:02.507Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-jamubc-gemini-mcp-tool","artifact":"https://unfragile.ai/mcp-jamubc-gemini-mcp-tool","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-jamubc-gemini-mcp-tool","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"}}