Sourcegraph Deep Search vs Decision Node
Detailed side-by-side comparison to help you choose the right tool
Sourcegraph Deep Search
🔴DeveloperDeveloper Tools
AI-assisted code search for investigating relationships and behavior across large codebases
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Starting Price
Starts at $16,000/year; annual minimumDecision Node
🔴DeveloperDeveloper Tools
MCP server that records development decisions as structured JSON, embeds them as vectors, and enables semantic search over past decisions.
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Starting Price
$0/monthFeature Comparison
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Sourcegraph Deep Search - Pros & Cons
Pros
- ✓Surfaces cross-repository relationships
- ✓Serves humans and agents through several interfaces
- ✓Enterprise deployment options
Cons
- ✗$16,000 minimum excludes small teams
- ✗AI credits add variable cost
- ✗Results need runtime verification
Decision Node - Pros & Cons
Pros
- ✓Semantic search finds relevant decisions even with different terminology
- ✓Works across all major AI coding tools via MCP
- ✓Local storage keeps sensitive decisions on-premises
- ✓Visual UI helps teams explore decision relationships
- ✓Structured format prevents decisions from becoming unstructured brain dumps
Cons
- ✗Requires a Gemini API key for vector embeddings (adds dependency and cost)
- ✗Only useful if the team consistently records decisions — needs adoption discipline
- ✗Local-only storage means no built-in team sync or cloud collaboration
- ✗Vector embeddings are Gemini-specific — no choice of embedding provider
- ✗No integration with existing decision documentation tools (ADR tools, Notion, etc.)
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