docs/CONTINUE_DEV_INTEGRATION.md

Continue.dev Integration Guide

This guide covers two approaches for integrating OpenProblems spatial transcriptomics documentation with Continue.dev:

1. Enhanced MCP Server (Primary approach - what we've built)
2. Continue.dev Document Artifacts (Alternative approach)

🎯 Approach 1: Enhanced MCP Server (RECOMMENDED)

Our OpenProblems MCP Server now provides real, comprehensive documentation from official sources through the Model Context Protocol.

Features

✅ Real-time documentation access from official sources ✅ Structured knowledge delivery via MCP Resources ✅ File system operations for local development ✅ Environment validation and setup assistance ✅ Pipeline creation and validation ✅ Automated documentation updates

Setup

1. Install Dependencies

pip install -e .

2. Download Real Documentation

openproblems-mcp download-docs

This command downloads and caches:

• Nextflow Documentation - Complete official docs from nextflow.io
• Viash Documentation - Comprehensive guides from viash.io
• OpenProblems Documentation - READMEs and guides from GitHub repositories
• Docker Best Practices - Bioinformatics-specific containerization patterns
• Spatial Workflow Templates - Ready-to-use pipeline templates

3. Configure Continue.dev

Add to your Continue.dev configuration (~/.continue/config.json):

{
  "mcpServers": {
    "openproblems": {
      "command": "python",
      "args": ["-m", "mcp_server.main"],
      "cwd": "/path/to/SpatialAI_MCP"
    }
  }
}

4. Verify Integration

openproblems-mcp doctor --check-tools
openproblems-mcp info

Continue.dev Workflow Example

Once configured, Continue.dev agents can:

// Agent can access comprehensive documentation
const nextflowDocs = await mcp.readResource("documentation://nextflow");
const spatialTemplates = await mcp.readResource("templates://spatial-workflows");

// Agent can perform file operations
const projectFiles = await mcp.callTool("list_directory", { directory_path: "." });
const pipelineContent = await mcp.callTool("read_file", { file_path: "main.nf" });

// Agent can validate and create pipelines
const validation = await mcp.callTool("validate_nextflow_config", {
  pipeline_path: "main.nf"
});

// Agent can check environment setup
const environment = await mcp.callTool("check_environment", {});

Available MCP Resources

Resource URI	Content	Size
documentation://nextflow	Complete Nextflow docs	~50KB+
documentation://viash	Complete Viash docs	~30KB+
documentation://docker	Bioinformatics Docker patterns	~10KB
templates://spatial-workflows	Spatial pipeline templates	~15KB
server://status	Server status and capabilities	~1KB

Available MCP Tools

Tool	Description	Use Case
read_file	Read file contents	Analyze configs, scripts
write_file	Create/modify files	Generate pipelines, configs
list_directory	Navigate project structure	Explore repositories
check_environment	Validate tool installation	Setup verification
validate_nextflow_config	Pipeline syntax checking	Quality assurance
run_nextflow_workflow	Execute pipelines	Testing and deployment
build_docker_image	Container preparation	Environment setup
analyze_nextflow_log	Debug pipeline errors	Troubleshooting

---

🔄 Approach 2: Continue.dev Document Artifacts (ALTERNATIVE)

For users who prefer to manage documentation directly in Continue.dev:

Setup

1. Download Documentation

openproblems-mcp download-docs
cd data/docs_cache

2. Add to Continue.dev Documents

In Continue.dev, add these cached documentation files as document artifacts:

data/docs_cache/nextflow_docs.md
data/docs_cache/viash_docs.md
data/docs_cache/openproblems_docs.md
data/docs_cache/docker_docs.md
data/docs_cache/spatial_templates_docs.md

3. Configure Continue.dev

Add to ~/.continue/config.json:

{
  "docs": [
    {
      "title": "Nextflow Documentation",
      "startUrl": "file:///path/to/SpatialAI_MCP/data/docs_cache/nextflow_docs.md"
    },
    {
      "title": "Viash Documentation",
      "startUrl": "file:///path/to/SpatialAI_MCP/data/docs_cache/viash_docs.md"
    },
    {
      "title": "OpenProblems Documentation",
      "startUrl": "file:///path/to/SpatialAI_MCP/data/docs_cache/openproblems_docs.md"
    },
    {
      "title": "Docker Best Practices",
      "startUrl": "file:///path/to/SpatialAI_MCP/data/docs_cache/docker_docs.md"
    },
    {
      "title": "Spatial Pipeline Templates",
      "startUrl": "file:///path/to/SpatialAI_MCP/data/docs_cache/spatial_templates_docs.md"
    }
  ]
}

Pros and Cons

	MCP Server Approach	Document Artifacts Approach
Pros	• Real-time access • Structured delivery • File operations • Tool execution	• Simple setup • Direct file access • No server dependency
Cons	• Requires MCP setup • More complex	• Manual updates • No tool execution • Static content

---

🏆 Recommendation: Use Enhanced MCP Server

The Enhanced MCP Server approach is recommended because:

1. Real-time Documentation - Always up-to-date with official sources
2. Interactive Capabilities - Agent can perform actions, not just read docs
3. Structured Knowledge - Organized, searchable, contextual information
4. Complete Workflow - From documentation to execution
5. Environment Integration - Validates setup and provides guidance

Example Continue.dev Agent Conversation

🧬 User: "Help me create a spatial transcriptomics quality control pipeline"

🤖 Agent: Let me help you with that! I'll:
1. Check your environment setup
2. Get the latest Nextflow best practices
3. Use spatial transcriptomics templates
4. Create an optimized pipeline for you

[Agent uses MCP tools to check environment, read documentation, and create pipeline]

✅ Agent: "I've created a spatial QC pipeline following OpenProblems standards.
The pipeline includes:
- Scanpy-based quality control
- Proper Docker containerization
- DSL2 Nextflow syntax
- Resource management
- Output publishing

Would you like me to validate the syntax and explain any part?"

---

🔧 Maintenance

Updating Documentation

# Refresh all documentation
openproblems-mcp download-docs

# Check server status
openproblems-mcp doctor

# Test integration
openproblems-mcp tool check_environment

Monitoring

# View cached documentation
ls -la data/docs_cache/

# Check server resources
openproblems-mcp info

---

🚀 Next Steps

1. Set up the Enhanced MCP Server using Approach 1
2. Download real documentation with openproblems-mcp download-docs
3. Configure Continue.dev to connect to the MCP server
4. Test the integration with spatial transcriptomics workflows
5. Enjoy AI-assisted bioinformatics development!

The integration provides computational biologists with unprecedented AI assistance for spatial transcriptomics pipeline development, combining the power of Continue.dev with comprehensive, real-time bioinformatics knowledge.