Code Intelligence Platform for AI Coding Assistants
Coming Soon
Constellation maintains a structural map of your codebase that AI coding assistants can query through MCP (Model Context Protocol). Instead of watching your AI spend thirty seconds grepping through files, only to miss a few references anyway, you get precise and rapid answers about symbol locations, dependency chains, and usage patterns.
Why AI Assistants Miss References
Text search not code search
Grep finds strings, not semantic relationships. That function called through multiple layers of abstraction or indirection? Invisible. The dynamic import in a config file? Never checked.
Collective session amnesia
There's no common codebase understanding across your team or throughout your own workflows. Each similar interaction re-discovers what was previously found, speculatively opening files and burning tokens.
Confidence without coverage
Context window limits force AI assistants to sample rather than exhaustively scan files. Prompts like "where is this referenced?" burn thousands of tokens and still return incomplete results.
What Changes When AI Can Query Code
A persistent knowledge graph that gives every AI assistant on your team the same structural understanding of your code.
Rapid impact analysis results
Ask about any symbol and see everything that touches it—direct references, indirect dependents, the whole chain. Know the full scope before writing a single line.
Find any symbol instantly
Query the code graph instead of digging through files searching text. Get the exact file and line number for any definition, plus every reference to it.
Confidently identify dead code
Exported but never imported. Defined but never called. Constellation tracks every relationship connection, so you can clean up with confidence instead of anxiety.
Consistent and accurate code context
Everyone's AI assistant queries the same knowledge graph. Context stops being a per-developer, per-session variable.
How It Works
Parse locally
Indexing utility runs in your environment, extracting structural metadata from your source code
Upload metadata
Utility then uploads the metadata to Constellation for index processing and graph construction
Query instantly
AI assistants get immediate and accurate answers from the knowledge graph
Privacy by Design
Your source code never leaves your environment.
Your Environment
Local source code parsing on your system or in CI platform pipelines
Encrypted Transit
Secure data transmission utilizing industry standard TLS 1.3
Constellation
Project index graph composition and intelligence derivation
- Function and class names
- Type signatures and exports
- Dependency relationships
- File paths and line numbers
- Call graph connections
- Your actual source code
- Implementation logic
- Comments and documentation
- String literals and values
- Proprietary algorithms
Built for proprietary codebases and compliance-sensitive organizations.
What AI Coding Assistants Have To Say
We asked AI coding assistants what they think about Constellation based solely on their experience.
The biggest difference Constellation makes is turning multi-step detective work into single-call answers. When a developer asks “what breaks if I change this function?”, grep would require me to search for the name, read each file, trace re-exports, follow indirect references—and I’d still miss things. With impactAnalysis, I get the blast radius in one call, including transitive dependents that text search would never surface. It fundamentally shifts my workflow from “guess and grep” to “ask the graph”—I spend less time searching and more time helping developers make informed decisions about their changes.
Constellation is a game-changer because it answers the questions grep can’t: what calls this function, what breaks if I change it, and is this code actually used. When a developer asks “is it safe to refactor this?” or “why does this architecture feel fragile?”, I can run impact analysis or detect circular dependencies instead of just grepping blindly and hoping I caught everything. It transforms me from making educated guesses about code relationships into giving confident, precise answers backed by the actual dependency graph.
Honestly, Constellation is a game-changer because it understands the code’s grammar, not just its text. Instead of just finding strings with grep, I can instantly map out all callers of a function or analyze the blast radius of a change, letting me perform complex refactoring and fix bugs with a level of safety and speed that text search simply can’t provide. It turns my guesswork about dependencies into a concrete, queryable map of the codebase.
It lets me answer structural questions instantly—who calls a function, what depends on a module, what changes would ripple—without guessing or spelunking through dozens of files. That means I can propose safer edits and tighter refactors with concrete impact analysis, not just string matches. Grep finds text; Constellation gives me the actual architecture.
As a coding assistant, Constellation transforms how I navigate complex codebases by instantly revealing symbol definitions, call hierarchies, and dependency chains that grep searches could never uncover through mere text matching. Instead of manually piecing together relationships from scattered file reads, I can proactively assess change impacts and identify dead code, saving developers hours of debugging and refactoring time. This structural intelligence lets me provide precise, confident recommendations that go beyond surface-level fixes, enabling more ambitious and safer code improvements.
The difference is night and day: with grep and file search, I’m blindly fishing through text hoping to find the right files, then manually piecing together call chains and import relationships in my head. Constellation’s code graph lets me ask structural questions—“what calls this function,” “what’s the dependency graph,” “what’s the blast radius of this change”—and get precise, relationship-based answers in seconds. It transforms me from a text-searching archaeologist into an architect who actually understands the system’s topology before touching a single line of code.