Give your coding agents the system context they are missing.
Spectrum delivers structured, task-specific context to any MCP-compatible agent: business rules, dependencies, and constraints, in a fraction of the tokens the raw source files would take.
Sound familiar?
Cursor, Claude Code, Codex, and Copilot gather context by retrieval, which returns the passages that look most similar to the question. Much of the context an agent needs looks nothing like the question, because it is connected to the task through a dependency or a business rule, and retrieval cannot see that connection. Some of the context is written nowhere and exists only when several sources are read together. **An agent needs a map of how the facts connect, and retrieval does not provide one.**
The result is code that compiles and violates a constraint only someone who knows the system would catch. The developer reviews it, rejects it, adds context, and tries again, and for a non-trivial task this cycle repeats several times.
Architectural decisions
Why the service is split the way it is.
Business rules
Which constraints apply to the code it is writing.
Dependencies
Which services break if this one changes.
Chunk retrieval (RAG)
It returns passages that look similar to the task, so the agent gets related text but not the rules that connect it, and no signal when two passages disagree or which one is correct.
Let the agent explore the repo
It reads files one at a time, never sees which service calls which, and runs out of context before it reaches the design document that explains why the code looks the way it does.
Meet Spectrum
Spectrum exposes the context layer as an MCP context source. Chunk retrieval returns text the agent still has to interpret. Spectrum returns facts, scoped to the current task: the relevant rules, dependencies, constraints, and decisions, and nothing unrelated.
Higher first-attempt accuracy
The agent knows the constraints before it writes code, so the first version respects them.
Facts with provenance
Each fact links to the lines, sections, or comments it came from. When the agent needs more detail, it knows exactly where to look, so the facts also work as a map of your sources.
Distilled knowledge instead of raw sources
The agent reasons over facts that were extracted and reconciled in advance, each held once however many sources state it, instead of working it out from the sources during the task.
The whole system, not one repository
Components spread across several repositories, trackers, and wikis form one context layer, so the agent sees dependencies that cross repository boundaries, and decisions and constraints recorded outside the code.
Fewer tokens per task
The server returns only the part of the context layer the task touches. Structured facts replace the raw file dump.
One integration
Connect Spectrum once, and every MCP-compatible agent in the toolchain uses the same context layer.
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