Crawler Summary

@houtini/gemini-mcp answer-first brief

Professional Model Context Protocol server for Google Gemini AI models with enterprise-grade features @houtini/gemini-mcp $1 $1 $1 ${badge_line} **I've been running this MCP server in my Claude Desktop setup for several months, and it's one of the few I leave enabled permanently.** Not because Gemini replaces Claude -- it doesn't -- but because grounded search, deep research, image generation, and video are things Gemini does well. Having them as tools inside Claude beats switching between browser tabs. Thirteen tool Capability contract not published. No trust telemetry is available yet. 6 GitHub stars reported by the source. Last updated 2/25/2026.

Freshness

Last checked 2/25/2026

Best For

@houtini/gemini-mcp is best for mcp, model-context-protocol, gemini workflows where MCP compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB MCP, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 89/100

@houtini/gemini-mcp

Professional Model Context Protocol server for Google Gemini AI models with enterprise-grade features @houtini/gemini-mcp $1 $1 $1 ${badge_line} **I've been running this MCP server in my Claude Desktop setup for several months, and it's one of the few I leave enabled permanently.** Not because Gemini replaces Claude -- it doesn't -- but because grounded search, deep research, image generation, and video are things Gemini does well. Having them as tools inside Claude beats switching between browser tabs. Thirteen tool

MCPself-declared

Public facts

4

Change events

0

Artifacts

0

Freshness

Feb 25, 2026

Verifiededitorial-contentNo verified compatibility signals6 GitHub stars

Capability contract not published. No trust telemetry is available yet. 6 GitHub stars reported by the source. Last updated 2/25/2026.

6 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

MCP

Freshness

Feb 25, 2026

Vendor

Houtini

Artifacts

0

Benchmarks

0

Last release

2.2.0

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 6 GitHub stars reported by the source. Last updated 2/25/2026.

Setup snapshot

git clone https://github.com/houtini-ai/gemini-mcp.git
  1. 1

    Setup complexity is MEDIUM. Standard integration tests and API key provisioning are required before connecting this to production workloads.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Houtini

profilemedium
Observed Feb 25, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

MCP

contractmedium
Observed Feb 25, 2026Source linkProvenance
Adoption (1)

Adoption signal

6 GitHub stars

profilemedium
Observed Feb 25, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB MCP

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Executable Examples

json

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": ["@houtini/gemini-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

bash

git clone https://github.com/houtini-ai/gemini-mcp
cd gemini-mcp
npm install --include=dev
npm run build

json

{
  "mcpServers": {
    "gemini": {
      "command": "node",
      "args": ["C:/path/to/gemini-mcp/dist/index.js"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

text

Use gemini:gemini_chat to ask: "What changed in the MCP spec in the last month?"

text

Use gemini:gemini_deep_research with:
  research_question="What are the current approaches to AI agent memory management?"
  max_iterations=5

text

Use gemini:generate_image with:
  prompt="Stock price chart showing Apple (AAPL) closing prices for the last 5 trading days"
  use_search=true
  aspectRatio="16:9"

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB MCP

Docs source

GITHUB MCP

Editorial quality

ready

Professional Model Context Protocol server for Google Gemini AI models with enterprise-grade features @houtini/gemini-mcp $1 $1 $1 ${badge_line} **I've been running this MCP server in my Claude Desktop setup for several months, and it's one of the few I leave enabled permanently.** Not because Gemini replaces Claude -- it doesn't -- but because grounded search, deep research, image generation, and video are things Gemini does well. Having them as tools inside Claude beats switching between browser tabs. Thirteen tool

Full README

@houtini/gemini-mcp

npm version MCP Registry Known Vulnerabilities ${badge_line}

I've been running this MCP server in my Claude Desktop setup for several months, and it's one of the few I leave enabled permanently. Not because Gemini replaces Claude -- it doesn't -- but because grounded search, deep research, image generation, and video are things Gemini does well. Having them as tools inside Claude beats switching between browser tabs.

Thirteen tools. One npx command.

MCP App previews

Generated images and diagrams render inline in Claude Desktop with zoom controls, file paths, and prompt context:

| Image generation | SVG / diagram generation | |:---:|:---:| | Image preview in MCP App | Diagram preview in MCP App |


Get started in two minutes

Step 1: Get a Gemini API key

Go to Google AI Studio and create one. The free tier covers most development use -- you'll hit rate limits on deep research if you're hammering it, but for day-to-day work it's fine.

Step 2: Add to your Claude Desktop config

Config file locations:

  • Windows: C:\Users\{username}\AppData\Roaming\Claude\claude_desktop_config.json
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": ["@houtini/gemini-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Step 3: Restart Claude Desktop

That's it. The tools show up automatically. npx pulls the package on first run -- no separate install.

Local build instead

For development, or if you'd rather not rely on npx:

git clone https://github.com/houtini-ai/gemini-mcp
cd gemini-mcp
npm install --include=dev
npm run build

Then point your config at the local build:

{
  "mcpServers": {
    "gemini": {
      "command": "node",
      "args": ["C:/path/to/gemini-mcp/dist/index.js"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

What it does

Chat with Google Search grounding

Use gemini:gemini_chat to ask: "What changed in the MCP spec in the last month?"

Grounding is on by default. Gemini searches Google before answering, so you get current information rather than training data cutoff answers. Sources come back as markdown links.

For questions where you want reasoning over live search -- "explain this code" or similar -- set grounding: false.

Supports thinking_level on Gemini 3 models: high for maximum reasoning depth, low to keep it fast, medium/minimal on Gemini 3 Flash only.

Deep research

Use gemini:gemini_deep_research with:
  research_question="What are the current approaches to AI agent memory management?"
  max_iterations=5

Runs multiple grounded search iterations, then synthesises a full report. Takes 2-5 minutes depending on complexity. Worth it for anything where you need comprehensive coverage rather than a quick answer.

Set max_iterations to 3-4 in Claude Desktop (4-minute tool timeout). In IDEs (Cursor, Windsurf, VS Code) or agent frameworks with longer timeout tolerance, 7-10 iterations produces noticeably better synthesis. Pass focus_areas as an array to steer toward specific angles.

Image generation with search grounding

Use gemini:generate_image with:
  prompt="Stock price chart showing Apple (AAPL) closing prices for the last 5 trading days"
  use_search=true
  aspectRatio="16:9"

Default model is gemini-3-pro-image-preview (Nano Banana Pro). Also supports gemini-2.5-flash-image for faster generation.

When use_search=true, Gemini searches Google for current data before generating. Financial and news queries work reliably and return 2-5 grounding sources as markdown links. Weather queries are inconsistent (Gemini API limitation, not a code issue).

Video generation with Veo 3.1

Use gemini:generate_video with:
  prompt="A close-up shot of a futuristic coffee machine brewing a glowing blue espresso, steam rising dramatically. Cinematic lighting."
  resolution="1080p"
  durationSeconds=8

Uses Google's Veo 3.1 model. Generates 4-8 second videos at up to 4K resolution with native synchronised audio. Processing takes 2-5 minutes -- the tool polls automatically until the video is ready.

Options worth knowing about:

  • aspectRatio -- 16:9 (landscape, default) or 9:16 (portrait/vertical)
  • generateAudio -- on by default, produces dialogue and sound effects matching the prompt
  • sampleCount -- generate up to 4 variations in one call
  • seed -- for deterministic output across runs
  • generateThumbnail -- extracts a frame via ffmpeg (needs ffmpeg in PATH)
  • generateHTMLPlayer -- creates a local HTML player alongside the video

SVG generation

Use gemini:generate_svg with:
  prompt="Architecture diagram showing a microservices system with API gateway, three services, and a shared database"
  style="technical"
  width=1000
  height=600

Generates clean, production-ready SVG code for diagrams, illustrations, icons, and data visualisations. Styles: technical (diagrams), artistic (illustrations), minimal (simple), data-viz (charts).

Image editing and analysis

Conversational editing -- Gemini 3 Pro Image maintains context across editing turns using thought signatures. The server captures these automatically. Pass them back on subsequent edit calls for full continuity:

Use gemini:edit_image with:
  prompt="Change the colour scheme to blue and green"
  images=[{data: imageBase64, mimeType: "image/png", thoughtSignature: "fromPreviousCall"}]

Skip thought signatures and each edit starts from scratch.

Analysis -- two tools for different purposes:

  • describe_image -- Fast general descriptions using Gemini 3 Flash
  • analyze_image -- Structured extraction and detailed reasoning using Gemini 3.1 Pro

Load local files:

Use gemini:load_image_from_path with filePath="C:/screenshots/error.png"

Returns base64 data ready for any image tool.

Media resolution control

Reduce token usage by up to 75% whilst maintaining quality:

| Level | Tokens | Savings | Best for | |-------|--------|---------|----------| | MEDIA_RESOLUTION_LOW | 280 | 75% | Simple tasks, bulk operations | | MEDIA_RESOLUTION_MEDIUM | 560 | 50% | PDFs/documents (OCR saturates here) | | MEDIA_RESOLUTION_HIGH | 1120 | default | Detailed analysis | | MEDIA_RESOLUTION_ULTRA_HIGH | 2000+ | per-image only | Maximum detail |

For PDF OCR, MEDIUM gives identical text extraction quality to HIGH at half the tokens. Set global_media_resolution to apply to all images, or override per-image with mediaResolution.

Landing page generation

Use gemini:generate_landing_page with:
  brief="A SaaS tool that helps developers monitor API latency"
  companyName="PingWatch"
  primaryColour="#6366F1"
  style="startup"
  sections=["hero", "features", "pricing", "cta"]

Returns a self-contained HTML file -- inline CSS and vanilla JS, no external dependencies. Styles: minimal, bold, corporate, startup.

Professional chart design systems

The gemini_prompt_assistant tool includes 9 professional chart design systems:

| System | Inspiration | Best for | |--------|------------|----------| | storytelling | Cole Nussbaumer Knaflic | Executive presentations -- everything muted except one bold highlight | | financial | Financial Times | Editorial journalism -- FT Pink background, serif titles | | terminal | Bloomberg / Fintech | High-density dark mode with electric neon | | modernist | W.E.B. Du Bois | Bold geometric blocks, stark contrasts | | professional | IBM Carbon / Tailwind | Enterprise dashboards | | editorial | FiveThirtyEight / Economist | Data journalism | | scientific | Nature / Science | Academic rigour | | minimal | Edward Tufte | Maximum data-ink ratio | | dark | Observable | Modern dark mode |

Use gemini:gemini_prompt_assistant with:
  request_type="template"
  use_case="product"
  desired_outcome="Generate a professional product comparison chart"

Help system

Use gemini:gemini_help with topic="overview"

Documentation for all features without leaving Claude. Topics: overview, image_generation, image_editing, image_analysis, chat, deep_research, grounding, media_resolution, models, all.


Image output and storage

Default behaviour: Images return as inline base64 previews (quality 100, 1024px) rendered directly in Claude.

Persistent storage: Set GEMINI_IMAGE_OUTPUT_DIR to auto-save all generated images:

"env": {
  "GEMINI_API_KEY": "your-api-key-here",
  "GEMINI_IMAGE_OUTPUT_DIR": "C:/Users/username/Pictures/gemini-output"
}

Every image saves with a timestamp filename. The tool returns both the inline preview and the file path.

Per-call override: Pass outputPath on any generation tool to save to a specific location.

The server uses a two-tier compression approach to handle the MCP protocol's ~1MB JSON-RPC limit whilst preserving full-resolution files on disk:

| Tier | Quality | Max dimension | Purpose | |------|---------|---------------|---------| | Full-res | Original | Original | Saved to disk | | Viewer preview | 100 | 1024px | MCP App inline preview (~400KB) |

Gemini returns 2-5MB images. The full image is saved to disk immediately, and a compressed preview is created for the MCP App viewer.


Configuration reference

| Variable | Required | Default | Description | |----------|----------|---------|-------------| | GEMINI_API_KEY | Yes | -- | Google AI API key from AI Studio | | GEMINI_DEFAULT_MODEL | No | gemini-3.1-pro-preview | Default model for gemini_chat and analyze_image | | GEMINI_DEFAULT_GROUNDING | No | true | Enable Google Search grounding by default | | GEMINI_IMAGE_OUTPUT_DIR | No | -- | Auto-save directory for generated images | | GEMINI_ALLOW_EXPERIMENTAL | No | false | Include experimental/preview models in auto-discovery | | GEMINI_MCP_LOG_FILE | No | false | Write logs to ~/.gemini-mcp/logs/ | | DEBUG_MCP | No | false | Log to stderr for debugging tool calls |


Tools reference

| Tool | Description | |------|-------------| | gemini_chat | Chat with Gemini 3.1 Pro. Google Search grounding on by default. Supports thinking_level for Gemini 3 | | gemini_deep_research | Multi-step iterative research with Google Search. Synthesises comprehensive reports | | gemini_list_models | Lists available models from the API | | gemini_help | Documentation for all features without leaving Claude | | gemini_prompt_assistant | Expert guidance for image generation with 9 chart design systems | | generate_image | Image generation with search grounding and thought signatures for conversational editing | | edit_image | Edit images with natural-language instructions. Supports multi-turn continuity | | describe_image | Fast image descriptions using Gemini 3 Flash | | analyze_image | Structured extraction and analysis using Gemini 3.1 Pro | | load_image_from_path | Read a local image file and return base64 for any image tool | | generate_video | Video generation with Veo 3.1 -- 4-8 seconds at up to 4K with native audio | | generate_svg | Production-ready SVG graphics for diagrams, illustrations, and data visualisations | | generate_landing_page | Self-contained HTML landing pages with inline CSS/JS |


Model reference

| Model | Used by | Notes | |-------|---------|-------| | gemini-3.1-pro-preview | gemini_chat, analyze_image | Default. Advanced reasoning | | gemini-3-pro-image-preview | generate_image, edit_image | Nano Banana Pro -- highest quality generation | | gemini-2.5-flash-image | generate_image (optional) | Faster generation, higher volume | | gemini-3-flash-preview | describe_image | Fast general descriptions | | veo-3.1-generate-preview | generate_video | Veo 3.1 -- 4K video with native audio |

Gemini 3 notes: Temperature is forced to 1.0 on Gemini 3 models (Google's requirement -- lower values cause looping). Thought signatures are captured automatically for conversational image editing. Thinking level only applies to gemini_chat.


Requirements

  • Node.js 18+
  • A Gemini API key from Google AI Studio
  • ffmpeg (optional, for video thumbnail extraction)

Licence

Apache-2.0

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB MCP

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

MCP: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/snapshot"
curl -s "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/contract"
curl -s "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITLAB_AI_CATALOGgitlab-mcp

Rank

83

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_PUBLIC_PROJECTSgitlab-mcp

Rank

80

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_AI_CATALOGrmcp-openapi

Rank

74

Expose OpenAPI definition endpoints as MCP tools using the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_AI_CATALOGrmcp-actix-web

Rank

72

An actix_web backend for the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "MCP"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_MCP",
      "generatedAt": "2026-04-17T02:37:43.354Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "MCP",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "mcp",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "model-context-protocol",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "gemini",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "google",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "ai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "llm",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "chatbot",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "typescript",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "nodejs",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "claude",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "anthropic",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "generative-ai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "machine-learning",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "artificial-intelligence",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "cli",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:MCP|unknown|profile capability:mcp|supported|profile capability:model-context-protocol|supported|profile capability:gemini|supported|profile capability:google|supported|profile capability:ai|supported|profile capability:llm|supported|profile capability:chatbot|supported|profile capability:typescript|supported|profile capability:nodejs|supported|profile capability:claude|supported|profile capability:anthropic|supported|profile capability:generative-ai|supported|profile capability:machine-learning|supported|profile capability:artificial-intelligence|supported|profile capability:cli|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Houtini",
    "href": "https://houtini.com/gemini-mcp/",
    "sourceUrl": "https://houtini.com/gemini-mcp/",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T03:09:34.611Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "MCP",
    "href": "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-02-25T03:09:34.611Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "6 GitHub stars",
    "href": "https://github.com/houtini-ai/gemini-mcp",
    "sourceUrl": "https://github.com/houtini-ai/gemini-mcp",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T03:09:34.611Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-houtini-ai-gemini-mcp/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[]

Sponsored

Ads related to @houtini/gemini-mcp and adjacent AI workflows.