The control plane
for Copilot, MCP servers,
and autonomous coding agents
11nines gives platform and security teams one place to govern every AI agent across the SDLC: enforce guardrails, audit every action, contain multi-agent runs, and cap Copilot spend — without slowing developers down.
Your developers ship with autonomous agents now. Copilot writes code, MCP servers reach into your systems, and multi-agent workflows open pull requests on their own. Most orgs have zero visibility into what those agents did, what they cost, and which guardrails they bypassed. 11nines closes that gap.
From first prompt to autonomous agent.
Based on the official GitHub Copilot quickstart. 11nines wraps every stage with guardrails, audit, and spend control — so your org can roll Copilot out broadly without losing visibility.
Sign up & pick a plan
Start on Copilot Free, or upgrade to Pro, Pro+, or Max for higher request limits and premium models. Organizations roll out via Copilot Business or Enterprise.
- Free · Pro · Pro+ · Max
- Business · Enterprise
- Org-wide policy controls
Ask Copilot Chat
Open the Copilot panel on github.com or in your IDE and ask questions about a file, a pull request, an issue, or a commit — in natural language.
- “Explain this file.”
- “How could I improve this code?”
- “Summarize this PR.”
Inline suggestions & agents
Get whole-function completions, next-edit suggestions, and let coding agents implement multi-file changes — all governed by your org's guardrails.
- Inline code completion
- Next edit suggestions
- Coding agent for multi-file tasks
Where Copilot agents touch the GitHub SDLC
Two views of the same system: the lifecycle loop developers ship through, and the runtime architecture that connects Copilot, MCP servers, and your repositories — all governed by the 11nines control plane.
Every stage above runs under guardrails, MCP permissions, forensic audit, and per-team budgets — enforced before the next agent action fires.
What goes wrong with agents in production — and what 11nines does about it.
Six concrete problems we hear from platform, security, and FinOps leaders rolling out Copilot, MCP, and coding agents at scale — each with the outcome 11nines delivers.
Agents in your SDLC, but no one owns them
Copilot, custom agents, and MCP servers ship code through CI without a clear owner, plan, or success criteria.
Every agent has an owner, a scoped repo set, defined inputs/outputs, and a CI workflow you can inspect.
Autonomous actions you can't approve or block
Agents branch, push, and open PRs on their own — bypassing change-control, security policy, and least-privilege.
Tiered autonomy levels with human-in-the-loop on risky actions. Policy violations are blocked at the gateway.
MCP servers exposed without a permission model
Agents call tools, secrets, and internal APIs through MCP servers with no allow-list and no per-tool scoping.
Centralized MCP allow-lists, per-agent tool permissions, and full traceability of every tool invocation.
Failures are invisible until production breaks
When a multi-agent run goes sideways, no one can replay the plan, the tool calls, or the prompts that caused it.
Forensic, immutable audit of every plan, decision, tool call, and artifact — queryable in real time.
Multi-agent runs collide and drift
Parallel agents overwrite each other's branches, duplicate work, hold stale context, and stall mid-task.
Isolation, conflict detection, drift alerts, and rollback playbooks for stuck or degraded multi-agent runs.
Copilot spend grows faster than usage
Idle seats, runaway premium-request consumption, and zero per-team budgets turn AI into a blank check.
Real-time seat optimization, per-team budgets, and hard spend caps enforced before the next request fires.