GITLAB_AI_CATALOGgitlab-mcp
Rank
83
A Model Context Protocol (MCP) server for GitLab
Traction
No public download signal
Freshness
Updated 2d ago
MCP
Crawler Summary
collaborative-ai-platform answer-first brief
MCP-First Collaborative Intelligence Platform with Aerial Intelligence & Professional CAD Generation 🤖 Collaborative AI Platform v2.0 **The world's first MCP-native collaborative intelligence platform with satellite-to-CAD capabilities** 🚀 Revolutionary Capabilities **🛰️ Aerial Intelligence Integration** - **Satellite imagery analysis** with ±3% measurement accuracy - **Professional CAD generation** (AutoCAD DXF, SVG, PDF) - **Real-world building intelligence** from any address globally - **Enhanced wind load cal Published capability contract available. No trust telemetry is available yet. Last updated 2/24/2026.
Freshness
Last checked 2/22/2026
Best For
Contract is available with explicit auth and schema references.
Not Ideal For
collaborative-ai-platform is not ideal for teams that need stronger public trust telemetry, lower setup complexity, or more explicit contract coverage before production rollout.
Evidence Sources Checked
editorial-content, capability-contract, runtime-metrics, public facts pack
Agent DossierGitHubSafety: 80/100
collaborative-ai-platform
MCP-First Collaborative Intelligence Platform with Aerial Intelligence & Professional CAD Generation 🤖 Collaborative AI Platform v2.0 **The world's first MCP-native collaborative intelligence platform with satellite-to-CAD capabilities** 🚀 Revolutionary Capabilities **🛰️ Aerial Intelligence Integration** - **Satellite imagery analysis** with ±3% measurement accuracy - **Professional CAD generation** (AutoCAD DXF, SVG, PDF) - **Real-world building intelligence** from any address globally - **Enhanced wind load cal
MCPverified
Public facts
6
Change events
1
Artifacts
0
Freshness
Feb 22, 2026
Verifiededitorial-content1 verified compatibility signal
Published capability contract available. No trust telemetry is available yet. Last updated 2/24/2026.
Schema refs publishedTrust evidence available
Trust score
Unknown
Compatibility
MCP
Freshness
Feb 22, 2026
Vendor
Mkidder97
Artifacts
0
Benchmarks
0
Last release
2.0.0
Executive Summary
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Published capability contract available. No trust telemetry is available yet. Last updated 2/24/2026.
Setup snapshot
git clone https://github.com/mkidder97/collaborative-ai-platform.git- 1
Setup complexity is MEDIUM. Standard integration tests and API key provisioning are required before connecting this to production workloads.
- 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.
Vendor (1)
Vendor
Mkidder97
profilemedium
Compatibility (2)
Protocol compatibility
MCP
contracthigh
Auth modes
mcp, api_key
contracthigh
Artifact (1)
Machine-readable schemas
OpenAPI or schema references published
contracthigh
Security (1)
Handshake status
UNKNOWN
trustmedium
Integration (1)
Crawlable docs
6 indexed pages on the official domain
search_documentmedium
Release & Crawl Timeline
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Artifacts Archive
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
6
Snippets
0
Languages
typescript
Executable Examples
text
MCP Foundation Layer
├── Document Processor (existing)
├── Construction Specialist (existing)
├── Quality Reviewer (existing)
├── Coordination Layer (existing)
└── Enhanced MCP Servers (new)
├── Aerial CAD Intelligence
├── Knowledge Base & Learning
└── Collaboration Protocolbash
node >= 18.0.0 npm or yarn
bash
git clone https://github.com/mkidder97/collaborative-ai-platform.git cd collaborative-ai-platform npm install
bash
# Create .env file with API keys GOOGLE_MAPS_API_KEY=your_google_maps_key OPENAI_API_KEY=your_openai_key # For agent intelligence
bash
# Start all MCP servers npm run mcp:all # Start main platform npm run dev
bash
# Input: Building address # Output: Professional construction package 1. Document Processor extracts address from project documents 2. Aerial CAD Intelligence captures satellite imagery and measurements 3. Construction Specialist performs enhanced wind calculations 4. Quality Reviewer validates against visual evidence 5. Professional deliverables generated (CAD drawings + reports)
Docs & README
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB MCP
Editorial quality
ready
MCP-First Collaborative Intelligence Platform with Aerial Intelligence & Professional CAD Generation 🤖 Collaborative AI Platform v2.0 **The world's first MCP-native collaborative intelligence platform with satellite-to-CAD capabilities** 🚀 Revolutionary Capabilities **🛰️ Aerial Intelligence Integration** - **Satellite imagery analysis** with ±3% measurement accuracy - **Professional CAD generation** (AutoCAD DXF, SVG, PDF) - **Real-world building intelligence** from any address globally - **Enhanced wind load cal
Full README
🤖 Collaborative AI Platform v2.0
The world's first MCP-native collaborative intelligence platform with satellite-to-CAD capabilities
🚀 Revolutionary Capabilities
🛰️ Aerial Intelligence Integration
- Satellite imagery analysis with ±3% measurement accuracy
- Professional CAD generation (AutoCAD DXF, SVG, PDF)
- Real-world building intelligence from any address globally
- Enhanced wind load calculations with actual penetration data
🤝 Genuine Agent Collaboration
- Agent-to-agent learning through standardized protocols
- Quality improvement through peer review and validation
- Cross-industry pattern recognition and knowledge transfer
- Autonomous workflow optimization based on collaboration success
🏗️ Construction Intelligence
- Document analysis → Aerial intelligence → CAD drawings → Engineering calculations
- Professional deliverables including AutoCAD-compatible drawings
- Wind load enhancement using real penetration detection (+14% accuracy)
- Complete construction packages with satellite imagery and technical documentation
🏛️ Architecture: Intelligence First, Interface Second
Built from genuine collaborative intelligence up to user interface, not the other way around. Every component serves real agent collaboration, not demo aesthetics.
MCP Foundation Layer
├── Document Processor (existing)
├── Construction Specialist (existing)
├── Quality Reviewer (existing)
├── Coordination Layer (existing)
└── Enhanced MCP Servers (new)
├── Aerial CAD Intelligence
├── Knowledge Base & Learning
└── Collaboration Protocol
🎯 Proven Agent Network
Universal Collaborative Agents
- Document Processor: PDF extraction, data parsing, address identification
- Quality Reviewer: Peer validation, accuracy assessment, recommendation generation
- Coordination Layer: Agent-to-agent communication and workflow management
Construction Specialist Agents
- Construction Specialist: Wind calculations, SOW generation, compliance checking
- Aerial CAD Intelligence: Satellite analysis, building measurement, professional CAD generation
Enhanced MCP Infrastructure
- Knowledge Base: Industry standards, collaboration patterns, cross-agent learning
- Collaboration Protocol: A2A communication, workflow optimization, quality validation
🛠️ Quick Start
Prerequisites
node >= 18.0.0
npm or yarn
Installation
git clone https://github.com/mkidder97/collaborative-ai-platform.git
cd collaborative-ai-platform
npm install
Environment Setup
# Create .env file with API keys
GOOGLE_MAPS_API_KEY=your_google_maps_key
OPENAI_API_KEY=your_openai_key # For agent intelligence
Start the Platform
# Start all MCP servers
npm run mcp:all
# Start main platform
npm run dev
🚀 Revolutionary Workflows
Satellite-to-CAD Construction Analysis
# Input: Building address
# Output: Professional construction package
1. Document Processor extracts address from project documents
2. Aerial CAD Intelligence captures satellite imagery and measurements
3. Construction Specialist performs enhanced wind calculations
4. Quality Reviewer validates against visual evidence
5. Professional deliverables generated (CAD drawings + reports)
Cross-Agent Quality Enhancement
# Any agent work gets enhanced through collaboration
Agent Work → Collaboration Protocol → Peer Review → Enhanced Output
↓
Knowledge Base learns successful patterns for future improvement
📊 Measurable Results
Quality Improvements
- Wind Load Accuracy: +14% with aerial intelligence data
- Document Analysis: +17% through peer review validation
- Overall Project Quality: +15-25% through structured collaboration
- CAD Accuracy: ±3% dimensional precision from satellite measurements
Professional Deliverables
- AutoCAD DXF files compatible with industry software
- PDF drawings ready for stakeholder presentation
- SVG web drawings for online project management
- Enhanced engineering reports with embedded aerial imagery
🌍 Global Capabilities
Satellite Intelligence
- Any building address worldwide analyzable via satellite
- Real building measurements vs. estimated dimensions
- Equipment detection (HVAC, vents, skylights) with wind impact analysis
- Professional documentation with embedded aerial photography
Cross-Industry Application
- Construction: Enhanced wind calculations and site analysis
- Real Estate: Property analysis and market intelligence
- Engineering: Structural analysis with real-world validation
- Insurance: Risk assessment with actual building data
🔧 MCP Server Architecture
Aerial CAD Intelligence MCP
# Tools provided:
- capture_aerial_intelligence
- generate_professional_cad
- create_construction_package
# Resources:
- aerial://cache/imagery
- aerial://cad/templates
Knowledge Base MCP
# Tools provided:
- query_knowledge
- add_collaboration_pattern
- get_agent_context
# Resources:
- knowledge://construction/standards
- knowledge://collaboration/patterns
- knowledge://agents/capabilities
Collaboration Protocol MCP
# Tools provided:
- initiate_collaboration
- send_agent_message
- recommend_collaboration
- validate_collaboration_quality
# Resources:
- protocol://agents/registry
- protocol://collaborations/active
- protocol://history/patterns
📈 Development Roadmap
Phase 1: Enhanced MCP Foundation ✅
- Aerial CAD Intelligence MCP server
- Knowledge Base with collaboration learning
- Standardized A2A communication protocols
Phase 2: Advanced Collaboration (Next 30 days)
- Dynamic agent team formation
- Cross-industry pattern transfer
- Autonomous workflow optimization
Phase 3: Industry Expansion (Next 60 days)
- Real estate market analysis agents
- Small business automation agents
- Engineering compliance specialists
Phase 4: Enterprise Platform (Next 90 days)
- Multi-tenant architecture
- Advanced analytics dashboard
- API ecosystem for third-party integration
🏆 Competitive Advantages
Technical Moat
- First satellite-to-CAD platform in construction industry
- Collaborative intelligence that improves through agent interaction
- Real-world accuracy vs. estimated dimensions and calculations
- Professional deliverables included in automated workflows
Business Model
- Global scalability: Any address worldwide analyzable
- Premium deliverables: Professional CAD drawings command higher prices
- Network effects: More collaborations = smarter platform for everyone
- Cross-industry expansion: Proven agents work across multiple industries
🤝 Contributing
This platform demonstrates genuine collaborative intelligence - agents working together to produce measurably better outcomes than individual capabilities.
Agent Development Guidelines
- MCP-Native: Build directly on MCP tools, no abstraction layers
- Real Collaboration: Agents must improve each other's work measurably
- Quality Focus: Every feature must demonstrate concrete value
- Learning Integration: Successful patterns stored for platform improvement
Testing Philosophy
- No mock data: Test with real addresses and actual satellite imagery
- Measurable outcomes: Quality improvements must be quantifiable
- Cross-agent validation: Agents test each other's work
- Real-world scenarios: Use actual construction project requirements
📄 License
MIT License - See LICENSE for details
🌟 The Vision
Building collaborative intelligence so compelling that the interface becomes obvious - because you're showing what actually works, not what looks impressive.
This isn't just automation - it's intelligence that sees the world, collaborates to solve problems, and continuously improves through interaction.
Ready to deploy the future of collaborative AI? 🚀
npm run mcp:all && npm run dev
Your agents can now see buildings from space, collaborate through standardized protocols, and deliver professional outputs that don't exist anywhere else in the market.
Contract & API
Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
Contract coverage
Status
ready
Auth
mcp, api_key
Streaming
No
Data region
global
Protocol support
MCP: verified
Requires: mcp, lang:typescript
Forbidden: none
Guardrails
Operational confidence: medium
Contract is available with explicit auth and schema references.
Trust confidence is not low and verification freshness is acceptable.
Protocol support is explicitly confirmed in contract metadata.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/snapshot"
curl -s "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract"
curl -s "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/trust"
Reliability & Benchmarks
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
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
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.
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.
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": "ready",
"authModes": [
"mcp",
"api_key"
],
"requires": [
"mcp",
"lang:typescript"
],
"forbidden": [],
"supportsMcp": true,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": "https://github.com/mkidder97/collaborative-ai-platform#input",
"outputSchemaRef": "https://github.com/mkidder97/collaborative-ai-platform#output",
"dataRegion": "global",
"contractUpdatedAt": "2026-02-24T19:46:07.107Z",
"sourceUpdatedAt": "2026-02-24T19:46:07.107Z",
"freshnessSeconds": 4429910
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"MCP"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_MCP",
"generatedAt": "2026-04-17T02:17:57.178Z"
}
},
"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": "supported",
"confidenceSource": "contract",
"notes": "Confirmed by capability contract"
},
{
"key": "mcp",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "collaborative-ai",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "agent-intelligence",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "cross-industry-learning",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "aerial-intelligence",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "satellite-analysis",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "cad-generation",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "construction-automation",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "agent-collaboration",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "professional-deliverables",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
}
],
"flattenedTokens": "protocol:MCP|supported|contract capability:mcp|supported|profile capability:collaborative-ai|supported|profile capability:agent-intelligence|supported|profile capability:cross-industry-learning|supported|profile capability:aerial-intelligence|supported|profile capability:satellite-analysis|supported|profile capability:cad-generation|supported|profile capability:construction-automation|supported|profile capability:agent-collaboration|supported|profile capability:professional-deliverables|supported|profile"
}Facts JSON
[
{
"factKey": "docs_crawl",
"category": "integration",
"label": "Crawlable docs",
"value": "6 indexed pages on the official domain",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "MCP",
"href": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract",
"sourceType": "contract",
"confidence": "high",
"observedAt": "2026-02-24T19:46:07.107Z",
"isPublic": true
},
{
"factKey": "auth_modes",
"category": "compatibility",
"label": "Auth modes",
"value": "mcp, api_key",
"href": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract",
"sourceType": "contract",
"confidence": "high",
"observedAt": "2026-02-24T19:46:07.107Z",
"isPublic": true
},
{
"factKey": "schema_refs",
"category": "artifact",
"label": "Machine-readable schemas",
"value": "OpenAPI or schema references published",
"href": "https://github.com/mkidder97/collaborative-ai-platform#input",
"sourceUrl": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/contract",
"sourceType": "contract",
"confidence": "high",
"observedAt": "2026-02-24T19:46:07.107Z",
"isPublic": true
},
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Mkidder97",
"href": "https://github.com/mkidder97/collaborative-ai-platform#readme",
"sourceUrl": "https://github.com/mkidder97/collaborative-ai-platform#readme",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-02-24T19:43:14.176Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/mcp-mkidder97-collaborative-ai-platform/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "docs_update",
"title": "Docs refreshed: Sign in to GitHub · GitHub",
"description": "Fresh crawlable documentation was indexed for the official domain.",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
}
]