data-ai MCP Server
AI-powered spec generation and review using multi-repo code graph intelligence for backend teams that ship to production.
Discovered via github-seeds:mcp-hot and last synced 3mo ago.
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Check the source repository for the latest setup steps.
csharp
Models
List all services in the workspace graph
`us.anthropic.claude-sonnet-4-*`
`gpt-4o`, any deployment
`gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo`
`llama3`, `mistral`, any local model
typescript
php - id: auth-service repo: ../auth-service language: go llm: provider: anthropic # or: openai, ollama, aws, azure, gcp model: claude-sonnet-4-5-20250929 api_key: ${ANTHROPIC_API_KEY} context_budget: 100000 # Token limit for prompt context integrations: jira: url: https://yourcompany.atlassian.net email: [email protected] api_token: ${CORBELL_JIRA_API_TOKEN} # or paste directly project_key: ENG issue_type: Task # Task
jira ui Architecture graph browser serve --port (default 7433) --no-browser mcp Model Context Protocol server serve stdio transport for Claude Desktop / Cursor init Create workspace.yaml ``` </details> <details> <summary><strong>MCP – Model Context Protocol</strong></summary> Corbell exposes its architecture graph, code embeddings, and spec tools via MCP, so external AI platforms (Cursor, Claude Desktop, Antigravity) can query your codebase context directly. ### Available Tools
Query service dependencies, methods, and call paths
Auto-discover relevant services for a feature description
Semantic search across the code embedding index
`claude-sonnet-4-5`, `claude-haiku-4-5`
`claude-sonnet-4-5@20250514`
Languages