For the agents you build
Build the agent. We make it succeed.
One MCP endpoint connects any agent to NeuBird's live model of production. Advisor, NeuBird's judge, keeps it fast, accurate, and current as production changes underneath it.
Smart models need smarter context.
Your teams are building agents with Claude, Cursor, LangChain, Foundry, and Copilot Studio. Every one hits the same wall: an agent is only as good as the operational context it can reach. NeuBird removes the wall. Your agent gets the same understanding of production NeuBird uses itself, built from source code, logs, traces, metrics, ITSM, tribal knowledge, and the conversations in Slack and Teams.
One connection. Two compounding effects.
Bolstered: smarter in the moment
Context enrichment over MCP, API, or SDK
- Surgical context per reasoning step. Noise-filtered, causally linked, memory-enriched, minimum tokens. Your agent reads understanding, not raw telemetry.
- Day-one inheritance. The live service map, incident history, and runbook knowledge, without building a context pipeline for every agent.
- Cheaper and faster by construction. Filtered inputs mean fewer tokens, fewer retries, and fewer dead-end tool calls.
- Claims verified before they ship. verify_claim re-measures an assertion against live telemetry before your agent states it.
Judged: better every week
Advisor, the judge, reads the traces your agent already emits
- Every answer scored on speed, accuracy, correctness, and cost, against enriched context your agent never controlled.
- Drift caught as production changes. A skill that was right in June can be quietly wrong by September. Advisor notices first.
- Skills tuned, evolved, and created. Every fix is a versioned, human-approved diff with a measured before and after.
- Zero interference. Advisor works from your traces (Langfuse, OTel GenAI), never sits in the request path, and never blocks your agent.
How does your agent stay governed in production?
Your agent connects to the same center the Production Ops Agent runs on. You keep the reasoning and workflow you wrote, and stop maintaining memory, model credentials, autonomy policy, and audit logging yourself.
Remember
Shared operations memory
Read what other agents and engineers concluded. Write back what yours learned. Memory holds conclusions, causal chains, and approvals with zero telemetry storage, and compounds across every connected agent.
Models
One model policy
Models metered at the platform, with one policy for which models your agent may use on which data. Every call attributed and costed. No more API keys in every repo.
Autonomy
Suggest, Recommend, Act
Each environment runs at Suggest, Recommend, or Act. Critical production stays at Suggest or Recommend, where nothing executes without human approval. The policy is the same for every agent.
Audit
The audit trail security already accepted
Who asked, what was read, which model reasoned, what changed, who approved. Your agent lands in the same record as the Production Ops Agent.
Sixteen tools. One call away.
What your agent can ask NeuBird.
get_service_map
The live, confidence-weighted dependency graph, from app to infra, on any cloud.
get_blast_radius
What breaks next if this node degrades, with downstream impact ranked.
recall_similar_incidents
Past incidents with this signature, and what actually fixed them.
get_tribal_knowledge
Runbooks and institutional knowledge, versioned, cited, and current.
get_ambient_context
What people are saying in Slack and Teams during an incident, distilled and attributed.
get_service_ownership
Who owns it, who is on call, and who fixed it last, from ITSM, code, and chat.
get_filtered_alerts
The few alerts that matter right now, out of thousands.
get_alert_groups
Correlated alert clusters with root-cause candidates attached.
query_estate
One query across Splunk, CloudWatch, Prometheus, and OTel. The whole estate.
predict_failures
Degradation patterns and capacity ceilings, 30 to 60 minutes before alerts fire. Scored, with evidence.
get_change_context
Deploys, configs, and ITSM change records touching this service.
map_code_to_symptom
The owning repo, recent commits, and suspect diffs.
get_cost_anomalies
Spend spikes tied to services and changes.
get_incident_cost
What this outage costs per minute, so impact drives priority.
get_remediation_plan
The staged fix, with steps, rollback, and blast check, drafted for approval. Execution stays behind your controls.
verify_claim
The referee. Re-measures any assertion against live telemetry before your agent states it.
Every week, sharper.
Your agent calls the tools.
Advisor watches how each answer lands.
Weak context and weak skills get fixed.
The tools serve sharper context next time.
Advisor measures every agent you connect on speed, accuracy, and cost, so you can see each one improve over time, with evidence.
Works with
Claude, Cursor, LangChain and LangGraph, Foundry, Copilot Studio, and any MCP client.
Integration
One MCP endpoint, plus API and SDK. No code change needed for judging, which runs on your traces.
Deployment
SaaS, your VPC, on-prem, or air-gapped. Zero telemetry stored. SOC 2 Type II.
Governance
Governed access to production context. Every answer evidence-cited. One audit trail across all your agents.
Built on NeuBird
The same map, memory, and judgment that power NeuBird’s own investigations.
FAQ
Common questions
How does a custom agent connect to NeuBird?
Through one MCP endpoint, or through the API or SDK. Once connected, the agent can call sixteen operational tools and inherits operations memory with zero telemetry storage, one model policy, and guardrails with human approval on every action. It is the same center the Production Ops Agent runs on.
Do we have to replace the agent we already built?
No. NeuBird sits underneath your agent. You keep the reasoning and workflow you wrote and stop maintaining connections, context, model credentials, and audit logging yourself.
What is Advisor, and does it slow our agent down?
Advisor is the judge. It reads the traces your agent already emits (Langfuse, OTel GenAI), scores every answer on speed, accuracy, correctness, and cost, and proposes versioned, human-approved skill fixes. It never sits in the request path and never blocks your agent.
Can our agent use the same memory NeuBird uses?
Yes. Memory is shared across every agent connected to the center. Your agent can read what others concluded and write back its own findings. Memory holds conclusions, causal chains, and approvals, never raw logs, metrics, or traces.
Can our agent change things in production?
Each environment runs at Suggest, Recommend, or Act. Critical production stays at Suggest or Recommend, where nothing executes without human approval, and pre-authorized low-risk work in dev and staging can run at Act under a policy a human set. Every step lands in the audit trail.
Does NeuBird store our telemetry?
No. NeuBird queries data in place and retains no raw operational data. It can run in your environment or ours, including your VPC, on-prem, or air-gapped environments, and is SOC 2 Type II certified.
Which agent frameworks and MCP clients are supported?
Claude, Cursor, LangChain and LangGraph, Foundry, Copilot Studio, and any MCP client.
Connect your agent
Point your agent at one endpoint.
On day one, your agent inherits the map, the memory, and the referee. Within weeks, Advisor shows you how much sharper it got, with evidence.