The MCP stack we built—and the Claude agents we are shipping next
We lead with a production-oriented MCP layer that connects repositories, tools, and IDEs to Claude. On top of that foundation, we are building agentic systems that plan, call tools, and hand off to humans when it matters.
- Claude interprets repositories—not just files in isolation
- API surfaces extracted into collections teams can run
- Test generation and execution wired into developer workflow
- Designed for review: humans approve before anything ships
Hardened with teams who ship on short cycles and still own every regression. We’ll walk the full MCP path against your repo shape—ingest, reasoning, artifacts—in one live session.
Planning and decomposition
Break a goal into steps, select tools, and produce structured plans your team can edit before execution.
Tool-grounded execution
Call internal APIs, ticketing systems, and data stores through controlled interfaces—not brittle prompts.
Governance by design
Role-aware access, audit trails, and escalation paths so automation stops at the right human.
Research and synthesis
Ingest long documents, tickets, and threads; produce cited briefs, decisions, and open questions.
Incident and signal triage
Correlate logs, alerts, and runbooks; rank hypotheses and suggested next actions for on-call.
Spec to test surface
From OpenAPI or hand-written specs to collections, contract checks, and regression suites.
Policy and change review
Map rules to structured checklists; diff proposed changes against policy with explainable gaps.
Knowledge copilots
Ground answers in wikis, code, and tickets with retrieval, citations, and access control.
Release intelligence
Summarize diffs and risk, highlight untested paths, and suggest validation focused on blast radius.
Meeting and decision capture
Turn transcripts into actions, owners, and timelines with traceability back to source.
Cross-system orchestration
Agents that coordinate CRM, billing, and internal tools with explicit approval gates per step.
Custom evaluation loops
Human-rated quality loops and automated graders so models improve against your standard—not generic benchmarks.
If your problem looks like “many sources, judgment calls, and tools”—that is the shape we optimize for. Bring the workflow; we map it to MCP, Claude, and agents.
See MCP and agents in one conversation
We will walk through your repo shape, toolchain, and where agents should stop for human review.