Cut AI input tokens by ~56%, reduce costs and improve outcomes at the same time.
Most tokens are wasted finding context. Prism removes that step.
Prism is the code context engine for AI coding agents — Claude Code, Cursor, and any MCP client. It indexes your codebase into structured, searchable, explained knowledge so agents get the right context up front instead of burning tokens hunting for it — cutting AI input tokens by ~56% to reduce costs and improve outcomes at the same time.
Your codebase, indexed, searchable, and explained
Prism turns your repository into a code knowledge graph: every function, class, and module is parsed, embedded, and described in plain language. AI coding agents — Claude Code, Cursor, and any MCP client — query it for the exact context they need, so they stop burning input tokens reading file after file.
At a glance
Average Token reduction
Time searching for context
Context retrieval latency
Languages Supported
Navigation Tools
AI Agents read too much and still miss what matters.
They retry. You pay.
What's actually happening
AI Agents
Read file after file
Miss the right module
Try again
A 5k token task becomes 15k.
Developers
Search
Ask
Rebuild mental models
Weeks just to understand the system.
Same problem. Different symptoms.
How it works
Prism
Your codebase connects to Prism through webhooks, commits, and file watch. Prism indexes, embeds, and maps every file into a searchable knowledge base.
One intelligence layer, two channels, always in sync: AI agents access it through MCP tools that plug directly into AI agents like Cursor and Claude Code. Developers, architects, and engineering managers access it through the Console.
Try PrismWhy AI coding agents need Prism
Models are not the bottleneck — context is. Prism is the code context engine that gives AI coding agents structured, searchable, explained knowledge of your codebase, cutting wasted tokens and improving the quality of what they ship.
Hybrid code search that returns the right context
Prism answers an agent's question with four-way retrieval — semantic meaning, plain-language intent, keyword, and exact match — then reranks results by relevance and architectural importance. The agent gets the smallest useful slice of the codebase instead of whole files.
A dependency graph, not a flat file list
Prism parses every function, class, and module into a code knowledge graph and ranks them with PageRank over the import graph. The result is a top-down map of how a system actually fits together, so agents and developers start from architecture rather than guesswork.
Always current, one config block
Prism re-indexes only the files that change on each push, so context never goes stale. Drop its MCP server into Claude Code, Cursor, or any MCP client with a single config block — or call the REST API directly. No SDK to install, no agent to run.