InfraPilot
Enables infrastructure operations including provisioning, configuration, monitoring, compliance auditing, and auto-remediation through natural language, using Terraform and Ansible tools exposed over MCP.
README
InfraPilot ๐ฐ๏ธ
Agentic AI for infrastructure operations. A multi-agent system that provisions, monitors, validates compliance and auto-remediates cloud, network and security infrastructure โ built on Python, MCP, Anthropic Claude, Terraform and Ansible.
InfraPilot closes the full ops loop end-to-end: provision โ configure โ observe โ audit โ remediate โ re-audit, coordinated by a crew of specialised AI agents โ and it runs out of the box with no cloud account, no API key and no Terraform/Ansible binaries required (it transparently simulates execution when a binary is absent).
Why it exists
Most "AI for DevOps" demos stop at a chatbot that writes a Terraform snippet. InfraPilot models the operational loop an automation engineer actually owns: turning declarative intent into running infrastructure, watching it, proving it meets security/governance policy, and fixing drift automatically through code โ with every action typed, reported and auditable.
Architecture
Two ways to drive it (CLI or MCP) feed one orchestrator. The orchestrator runs a crew of five agents in sequence; each agent owns exactly one tool, and every tool runs through a single executor that either calls the real binary or falls back to a labelled simulation. Claude is an optional reasoning layer wired into the agents โ never a hard dependency.
flowchart TB
CLI["CLI ยท infrapilot run"] --> ORCH
MCPC["MCP client ยท Claude Desktop / Code"] --> MCPS["MCP server"] --> ORCH
subgraph ORCH["Orchestrator โ sequential ops loop"]
direction LR
P[Provisioner] --> C[Configurator] --> O[Observer] --> A[Compliance Auditor] --> R[Remediator]
R -. re-audit .-> A
end
CLAUDE["Anthropic Claude ยท optional<br/>anomaly triage ยท remediation rationale"] -. reasoning .-> ORCH
P --> TF[Terraform tool]
C --> AN[Ansible tool]
O --> MON[Monitoring tool]
A --> POL[Policy-as-code engine]
R --> REM[Remediation strategies]
TF --> EX
AN --> EX
MON --> EX
POL --> EX
REM --> EX
EX["Executor โ real binary if present, else simulated"] --> STATE[("Infra state ยท Terraform / Ansible")]
- One orchestrator, one job each. A dependency-free sequential loop coordinates the five agents; the whole thing runs in CI and is what the tests exercise โ no heavyweight agent framework to install or mock.
- Tools are the source of truth. Terraform, Ansible, monitoring, policy and
remediation logic live in
infrapilot/tools/, shared by both the CLI loop and the MCP server โ one implementation, two ways to drive it. - MCP-native.
infrapilot/mcp_server/exposes the tools over the Model Context Protocol, so Claude Desktop / Claude Code / any MCP client can run infra operations through natural language. - Claude optional. With
ANTHROPIC_API_KEYset, each agent calls Claude to triage anomalies and justify remediations. Without it, the loop still completes deterministically.
Quickstart
git clone https://github.com/Gsfrota/infra-pilot && cd infra-pilot
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
infrapilot demo # fully simulated end-to-end run โ no creds needed
Example output (abridged):
โญโโโโโโโโโโโโโโโโโโโโโโโโ InfraPilot run โโโโโโโโโโโโโโโโโโโโโโโโโฎ
โ engine=native llm=off compliance score=100.0/100 โ
โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ
provision ok 4 resources provisioned (simulated)
configure ok configuration applied (simulated)
observe warn 3 anomalies detected
audit error 3 violations, score 43.8
remediate ok 3 fixes applied, score 43.8 -> 100.0
Commands
| Command | What it does |
|---|---|
infrapilot demo |
Self-contained simulated run (no cloud/API key/binaries). |
infrapilot run |
Full loop; uses real terraform/ansible if installed. |
infrapilot run --no-remediate |
Audit + propose fixes without applying. |
infrapilot audit |
Compliance gate โ exits non-zero on any violation (great in CI). |
Use it from Claude (MCP)
pip install -e ".[mcp]"
infrapilot-mcp # serves the tools over MCP (stdio)
// claude_desktop_config.json
{
"mcpServers": {
"infrapilot": { "command": "infrapilot-mcp" }
}
}
Then ask Claude: "Provision the infra, audit it for security issues, and remediate anything critical."
How the loop works
- Provision โ
TerraformToolappliesinfra/desired_state.yaml(realterraform applyagainst the local/null/random providers when the binary is present; simulated otherwise). - Configure โ
AnsibleToolconverges host configuration via a playbook. - Observe โ
MonitoringToolingests a Prometheus-style telemetry snapshot and triages anomalies against thresholds. - Audit โ the policy-as-code engine evaluates every resource against
policies/policies.yaml; new governance rules are added in YAML, not code. - Remediate โ
RemediationToolmaps each violation to a least-privilege fix and applies it through the right IaC backend (Terraform or Ansible). - Re-audit โ the loop re-scores compliance to prove the drift is closed.
Policy-as-code
- id: SEC-001
name: "No SSH open to the internet"
severity: critical
resource_type: security_group
rule: no_ingress_cidr
params: { port: 22, forbidden_cidr: "0.0.0.0/0" }
remediation: restrict_sg_ingress
Built-in rules: required_tag, no_ingress_cidr, attribute_equals,
attribute_max. Built-in remediations: add_tag, restrict_sg_ingress,
enable_encryption, restart_service.
Project layout
infrapilot/
โโโ agents/ # role/goal/backstory crew
โโโ engines/ # the sequential orchestrator (native.py)
โโโ tools/ # terraform ยท ansible ยท monitoring ยท compliance ยท remediation
โโโ mcp_server/ # MCP server exposing the tools
โโโ llm.py # optional Anthropic Claude reasoning layer
โโโ reporting.py # rich console + JSON/Markdown artifacts
โโโ cli.py # typer CLI
infra/ # terraform/, ansible/, observability/, desired_state.yaml
policies/ # policy-as-code
tests/ # pytest suite (engine, compliance, monitoring, remediation)
Development
pip install -e ".[dev]"
ruff check . # lint
pytest # tests
infrapilot demo # smoke test the full loop
CI (GitHub Actions) runs ruff + pytest on 3.10/3.11/3.12 and additionally
installs real Terraform and Ansible to validate/lint the IaC.
Roadmap
- [ ] Real cloud providers behind a feature flag (AWS/GCP modules)
- [ ] Parallel agent execution where the loop allows it
- [ ] Drift detection on a schedule (cron / GitHub Actions)
- [ ] OPA/Rego policy backend option
License
MIT โ see LICENSE.
Built by Guilherme Frota Souza โ Infrastructure & Automation Engineer.
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