For teams building their own agents
You built the agent. Give it a center to run from.
You already wired a model to your alerts and it works. The hard part is everything around it: keeping context fresh as the estate drifts, deciding which models it may call on which data, and answering for what it changes in production. NeuBird is the center your agent connects to for all of that, over MCP, API, or SDK, so you keep building the part that is yours.
What the weekend prototype does not cover
The agent was the easy part.
Context that goes stale
The topology you hand-fed it on day one drifts by week three. Every new service, every renamed queue, every retired host is another prompt to maintain.
API keys in every repo
Each agent carries its own model credentials. Nobody can say which model reasoned over which data, or what the whole fleet costs this month.
No shared memory
Your agent learns something in Tuesday’s incident. The vendor agent in the observability tool learns nothing. Neither remembers it by Thursday.
Write access as a yes or no
Either the agent can touch production or it cannot. There is no mechanism for it to earn more scope as its record improves, and no audit trail security will accept.
How your agent uses the center
Connect once. Inherit everything.
Connect over MCP, API, or SDK
Your agent reaches the center through whichever interface fits: the NeuBird MCP server from Claude or Cursor, the REST API from a workflow, or the SDK from your own service.
Inherit connections, memory, and context
Every data source the center already connects to, every failure pattern it has learned, and the context engineering that decides what a question needs: your agent gets all of it without re-implementing any of it.
Act within the same boundary
Model calls route through governed model access. Actions go through earned write access. Everything your agent reads, reasons, or changes lands in the same audit trail as NeuBird’s own investigations.
Built for the people building agents
What the center gives your agent.
Live topology
Dependencies discovered from real traffic and kept current across releases. You stop maintaining a map by hand.
Shared memory
Read what other agents and engineers learned. Write back what yours learned. Knowledge compounds across the fleet.
Context engineering as a service
Ask for the context a question needs and get the assembled telemetry, topology, and history back, instead of every dashboard in the prompt.
Governed model access
One policy for which models your agent may use on which data, with every call attributed and costed. No more keys in the repo.
Earned write access
Your agent starts by proposing. As its approvals accumulate, its scope widens. The boundary is legible and the same for every agent.
The audit trail security already accepted
Who asked, what was read, which model reasoned, what changed, who approved. Your agent’s actions land in the record your security team already exports.
FAQ
Common questions
How does a custom agent connect to NeuBird?
Through the NeuBird MCP server, the REST API, or the SDK. Once connected, the agent inherits the center’s data connections, shared memory, context engineering, governed model access, and earned write access.
Do we have to replace the agent we already built?
No. The center sits underneath your agent. You keep the reasoning and workflow you wrote and stop maintaining connections, context, model credentials, and audit logging yourself.
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 learned and write back its own findings, and NeuBird’s own investigations benefit from both.
How is model access governed for our agent?
Governed model access applies one policy for which models any agent may call on which data. Your agent’s calls route through it and are attributed to the agent, the user, the question, and a cost.
Can our agent change things in production?
Within earned write access. It starts by proposing actions. As approvals accumulate for a class of action, that class can run on its own. Anything outside the boundary is proposed and waits for a human, and every step is in the audit trail.
Does NeuBird store our telemetry?
No. The center queries data in place and retains no raw operational data. It can run inside your VPC, on-prem, or air-gapped environment, and is SOC 2 Type II certified.
Which MCP clients are supported?
Any MCP-compatible client, including Claude and Cursor. See the interfaces page for the current list and setup details.
For teams building their own agents
Connect your agent to the center.
Walk through the MCP, API, and SDK paths and see what your agent inherits on day one.