{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-jamubc--gemini-mcp-tool","slug":"jamubc--gemini-mcp-tool","name":"gemini-mcp-tool","type":"mcp","url":"https://jamubc.github.io/gemini-mcp-tool/","page_url":"https://unfragile.ai/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-jamubc--gemini-mcp-tool__cap_0","uri":"capability://tool.use.integration.mcp.protocol.bridging.to.gemini.cli.with.request.response.translation","name":"mcp protocol bridging to gemini cli with request-response translation","description":"Implements a three-layer bridge pattern that translates incoming MCP protocol requests into Gemini CLI commands and marshals structured responses back through the MCP SDK. The server uses @modelcontextprotocol/sdk to handle MCP protocol handshakes, tool registration, and response serialization, while spawning Gemini CLI processes as child processes to execute analysis tasks. This architecture decouples the MCP client (Claude Desktop) from the Gemini CLI runtime, enabling async request handling and graceful error propagation.","intents":["Enable Claude Desktop to invoke Gemini's analysis capabilities without direct API integration","Route MCP tool calls to Gemini CLI subprocesses and collect structured results","Maintain protocol compliance while abstracting CLI invocation complexity"],"best_for":["Claude Desktop users wanting to leverage Gemini's large context window","Teams building multi-model AI workflows with MCP as the integration layer","Developers extending Claude's capabilities with external CLI tools"],"limitations":["Requires Gemini CLI to be installed and authenticated separately — no built-in credential management","CLI subprocess spawning adds latency overhead (~500ms-2s per request depending on Gemini model startup time)","No request queuing or connection pooling — each MCP call spawns a new CLI process","Error handling depends on Gemini CLI exit codes and stderr parsing — fragile to CLI version changes"],"requires":["Node.js ≥16.0.0","Google Gemini CLI installed and authenticated with valid API credentials","@modelcontextprotocol/sdk npm package","TypeScript runtime (tsx) for development"],"input_types":["MCP tool call requests with structured parameters","File paths and directory references via @ syntax","Natural language prompts and code snippets"],"output_types":["Structured MCP tool results (JSON)","Gemini CLI stdout/stderr captured as text","Error objects with exit codes and diagnostic messages"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_1","uri":"capability://data.processing.analysis.file.and.directory.reference.resolution.with.syntax.for.multimodal.analysis","name":"file and directory reference resolution with @ syntax for multimodal analysis","description":"Implements a file reference system using @ prefix notation (e.g., @src/main.js, @., @package.json) that resolves file paths and directory structures, then passes them to Gemini CLI for multimodal processing. The system parses @ tokens from user prompts, validates file existence, and constructs Gemini CLI arguments that include file content or directory trees. This enables users to reference local files directly in natural language prompts without manual copy-paste, leveraging Gemini's ability to process large file contexts in a single request.","intents":["Analyze specific files or entire codebases by referencing them with @ notation in prompts","Process configuration files, source code, and documentation without manual content extraction","Understand directory structure and relationships by analyzing multiple files in one Gemini request"],"best_for":["Developers analyzing large codebases or unfamiliar projects","Teams performing code reviews or architecture assessments","Users wanting to leverage Gemini's large token window for multi-file analysis"],"limitations":["@ syntax parsing is basic — no glob patterns or wildcard support, only explicit paths","No built-in file size limits — very large files (>100MB) may exceed Gemini's token limits","Directory traversal is not recursive by default — @. includes only immediate directory contents","Binary files and non-text formats are not handled — only text-based file analysis supported"],"requires":["Valid file paths relative to the working directory where MCP server is running","Read permissions on referenced files and directories","Gemini CLI with multimodal support enabled"],"input_types":["Natural language prompts containing @ file references","File paths (absolute or relative)","Directory paths"],"output_types":["File content or directory tree structures passed to Gemini","Analysis results from Gemini based on file context"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_10","uri":"capability://safety.moderation.error.handling.and.propagation.from.gemini.cli.with.exit.code.interpretation","name":"error handling and propagation from gemini cli with exit code interpretation","description":"Captures Gemini CLI exit codes, stdout, and stderr, interpreting them to construct meaningful error messages that are returned through the MCP protocol. The system treats non-zero exit codes as failures, extracts error details from stderr, and wraps them in MCP error responses. This approach provides visibility into Gemini CLI failures without requiring users to debug CLI output directly, though error messages depend on Gemini CLI's error formatting.","intents":["Understand why Gemini analysis failed without manually inspecting CLI output","Receive actionable error messages that guide troubleshooting","Distinguish between different failure modes (authentication, rate limiting, invalid input, etc.)"],"best_for":["Users troubleshooting integration issues","Teams building automated workflows that need to handle failures gracefully","Developers debugging MCP server behavior"],"limitations":["Error interpretation depends on Gemini CLI's error message format — changes to CLI output may break error parsing","Exit codes are generic (0 for success, non-zero for failure) — no structured error codes for different failure types","stderr output is captured as plain text — no structured error objects or error codes","Error messages may be cryptic or unhelpful if Gemini CLI does not provide detailed diagnostics","No retry logic — transient errors (rate limiting, temporary outages) are not automatically retried"],"requires":["Gemini CLI installed and executable","Valid Gemini API credentials","Understanding of Gemini CLI error messages"],"input_types":["Gemini CLI exit codes","stderr output from Gemini CLI","stdout output (if applicable)"],"output_types":["MCP error responses with error messages","Diagnostic information for troubleshooting","Exit codes and raw CLI output (for debugging)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_2","uri":"capability://code.generation.editing.sandbox.isolated.code.execution.with.gemini.s.execution.environment","name":"sandbox-isolated code execution with gemini's execution environment","description":"Provides a sandbox-test tool that routes code snippets to Gemini's isolated execution environment, allowing safe testing and validation of code without running it locally. The system accepts code input via the /sandbox slash command or sandbox-test tool, passes it to Gemini CLI with sandbox execution flags, and returns execution results including stdout, stderr, and exit codes. This leverages Gemini's built-in sandboxing to prevent malicious code execution while enabling rapid code testing within the Claude workflow.","intents":["Test code snippets safely without executing them on the local machine","Validate code behavior and debug issues using Gemini's execution environment","Prototype and iterate on code ideas with immediate feedback from a sandboxed runtime"],"best_for":["Developers prototyping code without local environment setup","Security-conscious teams avoiding local code execution","Users testing untrusted or experimental code snippets"],"limitations":["Sandbox environment is stateless — no persistent state between executions","Limited to languages supported by Gemini's sandbox (typically Python, JavaScript, and a few others)","Network access from sandbox is restricted — cannot make external API calls or access local services","Execution timeout limits apply (typically 30-60 seconds) — long-running processes will be terminated","File system access in sandbox is read-only or ephemeral — no persistent file creation"],"requires":["Gemini CLI with sandbox execution support enabled","Code input in a supported language (Python, JavaScript, etc.)","Valid Gemini API credentials with sandbox execution permissions"],"input_types":["Code snippets as text","Programming language specification","Input parameters or test data"],"output_types":["Execution stdout and stderr","Exit codes and error messages","Execution duration and resource usage metrics"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_3","uri":"capability://tool.use.integration.dual.interface.tool.invocation.with.natural.language.and.slash.commands","name":"dual-interface tool invocation with natural language and slash commands","description":"Exposes Gemini analysis capabilities through two complementary interfaces: natural language tool calls (ask-gemini tool) and structured slash commands (/analyze, /sandbox, /help, /ping). The MCP server registers both tool definitions in the MCP protocol, allowing Claude to invoke either interface based on context. Natural language tools enable flexible, conversational analysis requests, while slash commands provide explicit, structured invocation for power users. Both routes converge on the same underlying Gemini CLI execution logic, providing consistency while supporting different user preferences.","intents":["Invoke Gemini analysis using natural conversational language without learning command syntax","Use explicit slash commands for precise, repeatable analysis workflows","Switch between interfaces based on task context and user preference"],"best_for":["Mixed-skill teams with both technical and non-technical users","Workflows requiring both exploratory analysis and structured automation","Users familiar with slash command interfaces from other tools (Discord, Slack)"],"limitations":["Slash command parsing is rigid — no fuzzy matching or abbreviations, exact syntax required","Natural language tool calls depend on Claude's interpretation — ambiguous prompts may not route correctly","No command history or autocomplete — users must remember exact syntax","Parameter validation happens at Gemini CLI level, not in MCP server — errors may be cryptic"],"requires":["Claude Desktop or compatible MCP client that supports tool calling","MCP server running and registered with the client","Gemini CLI installed and authenticated"],"input_types":["Natural language prompts for ask-gemini tool","Slash command syntax with parameters (e.g., /analyze prompt:@file)","File references and code snippets"],"output_types":["Structured MCP tool results","Gemini analysis output as text","Help text and connection status messages"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_4","uri":"capability://planning.reasoning.multi.model.selection.with.gemini.model.variants.flash.pro.nano","name":"multi-model selection with gemini model variants (flash, pro, nano)","description":"Supports dynamic selection between multiple Gemini model variants (gemini-2.5-flash, gemini-pro, gemini-nano) by passing model selection flags to the Gemini CLI. The system allows users to specify which model to use for analysis tasks, enabling trade-offs between speed (flash), capability (pro), and cost/latency (nano). Model selection is passed through MCP tool parameters or environment configuration, and the MCP server constructs appropriate Gemini CLI arguments based on the selected model.","intents":["Choose faster models (flash) for quick analysis when latency is critical","Select more capable models (pro) for complex reasoning tasks requiring deeper analysis","Use cost-optimized models (nano) for high-volume analysis with acceptable accuracy trade-offs"],"best_for":["Teams with variable analysis requirements and cost sensitivity","Workflows where analysis speed varies by task (quick reviews vs. deep analysis)","Users optimizing for specific metrics (latency, cost, accuracy)"],"limitations":["Model availability depends on Gemini API tier and region — not all models available in all regions","No automatic model selection based on task complexity — users must choose manually","Model capabilities vary significantly — nano may fail on complex reasoning tasks","Switching models mid-workflow requires explicit parameter changes — no seamless fallback"],"requires":["Gemini CLI version supporting multiple model selection","API credentials with access to selected models","Knowledge of model capabilities and trade-offs"],"input_types":["Model name parameter (gemini-2.5-flash, gemini-pro, gemini-nano)","Analysis prompts and file references"],"output_types":["Analysis results from selected model","Model metadata (name, version, capabilities)"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_5","uri":"capability://safety.moderation.schema.based.tool.registration.and.parameter.validation.with.zod","name":"schema-based tool registration and parameter validation with zod","description":"Uses Zod schema validation to define tool parameters and validate inputs before passing them to Gemini CLI. The MCP server registers tools with structured schemas (ask-gemini, sandbox-test, etc.) that specify required parameters, types, and constraints. When Claude invokes a tool, the MCP server validates the parameters against the Zod schema, returning validation errors if parameters are malformed. This ensures that only valid inputs reach the Gemini CLI, reducing downstream errors and improving user experience.","intents":["Validate tool parameters before execution to catch errors early","Provide clear error messages when users supply invalid parameters","Enable Claude to understand tool parameter requirements through schema introspection"],"best_for":["Teams building robust MCP servers with strict input validation","Workflows where invalid parameters should fail fast rather than propagate","Systems requiring clear error messages and parameter documentation"],"limitations":["Zod validation adds ~10-50ms overhead per tool invocation","Schema definitions must be maintained separately from Gemini CLI argument construction — risk of drift","Complex validation rules (e.g., conditional parameters) are difficult to express in Zod schemas","Validation errors are returned to Claude but may not be actionable without detailed documentation"],"requires":["Zod npm package installed","TypeScript for schema definition","MCP SDK support for schema-based tool registration"],"input_types":["Tool parameters as JSON objects","Parameter types: string, number, boolean, array, object"],"output_types":["Validation success/failure status","Detailed validation error messages","Validated parameter objects passed to Gemini CLI"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_6","uri":"capability://automation.workflow.connection.health.checking.and.diagnostic.messaging.with.ping.and.help.commands","name":"connection health checking and diagnostic messaging with /ping and /help commands","description":"Provides /ping and /help slash commands that enable users to verify MCP server connectivity and understand available tools without executing analysis tasks. The /ping command sends a test message to the Gemini CLI and returns connection status, confirming that the MCP server, Gemini CLI, and API credentials are all functional. The /help command displays available tools, their parameters, and usage examples. These diagnostic tools reduce troubleshooting time and provide self-service documentation.","intents":["Verify that the MCP server and Gemini CLI are properly configured and connected","Understand available tools and their parameters without reading external documentation","Diagnose connectivity issues before attempting analysis tasks"],"best_for":["New users setting up the MCP server for the first time","Teams troubleshooting integration issues","Users wanting quick reference documentation within Claude"],"limitations":["/ping only tests basic connectivity — does not validate API quota or rate limits","/help text is static — does not reflect dynamic tool availability or model-specific capabilities","Diagnostic messages are text-based — no structured error codes or machine-readable status","No detailed logging or debug mode — troubleshooting requires manual CLI testing"],"requires":["MCP server running and registered with Claude Desktop","Gemini CLI installed and in PATH","Valid Gemini API credentials"],"input_types":["Test message for /ping (optional)","No parameters for /help"],"output_types":["Connection status message (success/failure)","Help text with tool descriptions and usage examples","Error messages if connection fails"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_7","uri":"capability://automation.workflow.asynchronous.subprocess.spawning.with.gemini.cli.process.management","name":"asynchronous subprocess spawning with gemini cli process management","description":"Manages Gemini CLI as child processes spawned asynchronously for each MCP tool invocation, using Node.js child_process APIs to handle subprocess lifecycle, I/O streams, and exit code handling. The system spawns a new Gemini CLI process per request, captures stdout and stderr, waits for process completion, and returns results through the MCP protocol. This architecture enables concurrent requests (each with its own process) and isolates failures to individual requests without affecting the MCP server.","intents":["Execute Gemini CLI commands asynchronously without blocking the MCP server","Handle multiple concurrent analysis requests by spawning independent processes","Capture and return Gemini CLI output through the MCP protocol"],"best_for":["High-concurrency scenarios with multiple simultaneous analysis requests","Workflows where request isolation is critical (one failed request should not affect others)","Systems requiring detailed subprocess output and error diagnostics"],"limitations":["Each request spawns a new Gemini CLI process — high overhead for frequent small requests","No connection pooling or process reuse — startup latency (~500ms-2s) per request","Subprocess output is buffered in memory — very large outputs (>100MB) may cause memory issues","Process termination is not graceful — timeout handling relies on Node.js process.kill() which may leave zombie processes","No built-in retry logic — failed requests are not automatically retried"],"requires":["Node.js ≥16.0.0 with child_process module","Gemini CLI executable in system PATH","Sufficient system resources (file descriptors, memory) for concurrent processes"],"input_types":["Gemini CLI command arguments and flags","stdin input (if applicable)","Environment variables"],"output_types":["Process stdout as text","Process stderr as text","Exit code (0 for success, non-zero for failure)","Process execution time"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_8","uri":"capability://code.generation.editing.typescript.based.mcp.server.implementation.with.type.safety","name":"typescript-based mcp server implementation with type safety","description":"Implements the entire MCP server in TypeScript using the @modelcontextprotocol/sdk, providing compile-time type checking for tool definitions, request handlers, and response objects. The system uses TypeScript interfaces to define tool schemas, request/response types, and error objects, catching type mismatches at build time rather than runtime. This approach reduces bugs related to parameter mismatches and enables IDE autocomplete for MCP protocol interactions.","intents":["Develop MCP servers with compile-time type safety and IDE support","Catch parameter and response type mismatches before deployment","Enable refactoring with confidence that type changes are propagated throughout the codebase"],"best_for":["Teams building production MCP servers with strict quality requirements","Developers familiar with TypeScript and preferring type safety","Projects requiring long-term maintainability and refactoring safety"],"limitations":["TypeScript compilation adds build time (~5-10 seconds) before execution","Type definitions must be maintained for all external APIs and CLI outputs — manual effort","Runtime errors can still occur if types are incorrectly defined (e.g., CLI output format changes)","Requires TypeScript knowledge — higher barrier to entry for JavaScript-only developers"],"requires":["TypeScript ≥4.5","Node.js ≥16.0.0","@modelcontextprotocol/sdk with TypeScript definitions","Build tooling (tsx or tsc) for compilation"],"input_types":["TypeScript source files","Tool schema definitions","Request handler implementations"],"output_types":["Compiled JavaScript","Type declaration files (.d.ts)","Source maps for debugging"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-jamubc--gemini-mcp-tool__cap_9","uri":"capability://automation.workflow.environment.based.configuration.for.gemini.api.credentials.and.model.selection","name":"environment-based configuration for gemini api credentials and model selection","description":"Supports configuration of Gemini API credentials and model selection through environment variables, allowing users to customize the MCP server behavior without modifying source code. The system reads environment variables (e.g., GEMINI_API_KEY, GEMINI_MODEL) at startup and passes them to the Gemini CLI as arguments or environment variables. This approach enables deployment flexibility — the same MCP server binary can be deployed to different environments with different configurations.","intents":["Configure API credentials securely without hardcoding them in source code","Select different Gemini models for different deployment environments (dev, staging, prod)","Enable users to customize MCP server behavior without rebuilding from source"],"best_for":["Teams deploying MCP servers across multiple environments","Security-conscious teams avoiding hardcoded credentials","Users wanting to customize model selection per deployment"],"limitations":["Environment variables are not encrypted — credentials are visible in process listings and logs","No validation of environment variables at startup — invalid credentials are only discovered when a tool is invoked","Configuration is static at startup — changing environment variables requires server restart","No built-in secrets management — teams must use external tools (e.g., .env files, secret managers) for credential storage"],"requires":["Environment variables set before MCP server startup","Gemini API key with appropriate permissions","Knowledge of supported environment variable names and formats"],"input_types":["Environment variable names and values","Configuration strings (model names, API endpoints)"],"output_types":["Parsed configuration objects","Validation status and error messages"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":46,"verified":false,"data_access_risk":"high","permissions":["Node.js ≥16.0.0","Google Gemini CLI installed and authenticated with valid API credentials","@modelcontextprotocol/sdk npm package","TypeScript runtime (tsx) for development","Valid file paths relative to the working directory where MCP server is running","Read permissions on referenced files and directories","Gemini CLI with multimodal support enabled","Gemini CLI installed and executable","Valid Gemini API credentials","Understanding of Gemini CLI error messages"],"failure_modes":["Requires Gemini CLI to be installed and authenticated separately — no built-in credential management","CLI subprocess spawning adds latency overhead (~500ms-2s per request depending on Gemini model startup time)","No request queuing or connection pooling — each MCP call spawns a new CLI process","Error handling depends on Gemini CLI exit codes and stderr parsing — fragile to CLI version changes","@ syntax parsing is basic — no glob patterns or wildcard support, only explicit paths","No built-in file size limits — very large files (>100MB) may exceed Gemini's token limits","Directory traversal is not recursive by default — @. includes only immediate directory contents","Binary files and non-text formats are not handled — only text-based file analysis supported","Error interpretation depends on Gemini CLI's error message format — changes to CLI output may break error parsing","Exit codes are generic (0 for success, non-zero for failure) — no structured error codes for different failure types","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.49926584101306354,"quality":0.47,"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":"2026-05-24T12:16:21.550Z","last_scraped_at":"2026-05-03T13:56:59.049Z","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=jamubc--gemini-mcp-tool","compare_url":"https://unfragile.ai/compare?artifact=jamubc--gemini-mcp-tool"}},"signature":"tOuGIEkPh54PYyfr8WQEB6kk7oyjOHAzuexUmVdcTegQviVs522g6kgi8cglB3sC9RF0wkIpArxO1aS3n5hPAg==","signedAt":"2026-06-20T00:12:51.333Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/jamubc--gemini-mcp-tool","artifact":"https://unfragile.ai/jamubc--gemini-mcp-tool","verify":"https://unfragile.ai/api/v1/verify?slug=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"}}