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MCP-Ambari-APISAFE

mcp/call518/mcp-ambari-api
MCP server by call518 · agentic ai · ai · ambari metrics · Audited 2026-10-11
⚑ Report / re-scanSource ↗

🚀 Natural-language Hadoop cluster management via MCP. Connect LLM agents (Claude, GPT, etc.) directly to Apache Ambari REST API — control services, inspect configs, query metrics, and manage alerts with AI. Built with FastMCP & aiohttp.

Verdict
SAFE
Grade
B
Trust score
89 /100
Exposed tools
1 1r · 0w · 0d
Transport
stdio · streamable-http
License
MIT
Stars
1
01

Overview

From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.

🚀 Automate Apache Ambari operations with AI/LLM: Conversational control for Hadoop cluster management, service monitoring, configuration inspection, and precise Ambari Metrics queries via Model Context Protocol (MCP) tools.

[](https://opensource.org/licenses/MIT) [](https://www.buymeacoffee.com/call518)

[](https://github.com/call518/MCP-Ambari-API/actions/workflows/pypi-publish.yml)

Architecture & Internal (DeepWiki)

[](https://deepwiki.com/call518/MCP-Ambari-API)

📋 Overview

MCP Ambari API is a powerful Model Context Protocol (MCP) server that enables seamless Apache Ambari cluster management through natural language commands. Built for DevOps engineers, data engineers, and system administrators who work with Hadoop ecosystems.

Features

  • ✅ Interactive Ambari Operations Hub – Provides an MCP-based foundation for querying and managing services through natural language instead of console or UI interfaces.
  • ✅ Real-time Cluster Visibility – Comprehensive view of key metrics including service status, host details, alert history, and ongoing requests in a single interface.
  • ✅ Metrics Intelligence Pipeline – Dynamically discovers and filters AMS appIds and metric names, connecting directly to time
Read from source at commit cd665c4f477cOBSERVED · 2026-10-11
02

Connect

Built from this server's own package name, version and transport as found in its source — not copied from anyone's documentation, so it cannot drift against a page we do not control. Replace the environment placeholders with a token scoped to the least it needs.

claude-code
claude mcp add mcp-ambari-api --env AMBARI_PASS=${AMBARI_PASS} --env REMOTE_AUTH_ENABLE=${REMOTE_AUTH_ENABLE} --env REMOTE_SECRET_KEY=${REMOTE_SECRET_KEY} -- uvx mcp-ambari-api
claude-desktop
{
  "mcpServers": {
    "mcp-ambari-api": {
      "command": "uvx",
      "args": [
        "mcp-ambari-api"
      ],
      "env": {
        "AMBARI_PASS": "${AMBARI_PASS}",
        "REMOTE_AUTH_ENABLE": "${REMOTE_AUTH_ENABLE}",
        "REMOTE_SECRET_KEY": "${REMOTE_SECRET_KEY}"
      }
    }
  }
}
03

Exposed tools (1)

1 read · 0 write · 0 destructive.

ToolRiskDescription
get_prompt_templatereadReturn the canonical English prompt template (optionally a specific section).
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
declared (4 observation(s))
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (1)

LOWInventory / provenance · inv.hidden_file · CWE-1104
.pre-commit-config.yaml
.pre-commit-config.yaml
Why it matters. hidden member outside the usual dotfiles
Fix. review its purpose

Gates applied: no_behavioural_pass.

Audited 2026-10-11 · audit v0.4.1 · source sha cd665c4f477cfull audit observations/trust-audit/mcp-server/call518__mcp-ambari-api.json · Report an issue / request a re-scan
05

Audit history

Every audit this server has had. A grade with a past is a grade somebody is still checking.

DateSourceVerdictGradeScoreChange
2026-10-11cd665c4f477cSAFEB89first audit
06

Questions

What is the MCP-Ambari-API MCP server?

🚀 Natural-language Hadoop cluster management via MCP. Connect LLM agents (Claude, GPT, etc.) directly to Apache Ambari REST API — control services, inspect configs, query metrics, and manage alerts with AI. Built with FastMCP & aiohttp.

What tools does MCP-Ambari-API expose?

1 in total: 1 read-only, 0 that write, and 0 that can delete or overwrite. Every one is listed on this page with its risk.

Is MCP-Ambari-API safe to connect to an agent?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean server reads B.

What credentials does MCP-Ambari-API need?

It reads AMBARI_PASS, REMOTE_AUTH_ENABLE and REMOTE_SECRET_KEY from the environment. Give it a token scoped to the least it needs — an agent that can be talked into calling a tool can be talked into calling it with your credentials.

How does MCP-Ambari-API run?

It speaks stdio and streamable-http, so it runs as a local process your client starts. It is published on PyPI as mcp-ambari-api.

How current is this page?

The grade is for one exact copy of the source (cd665c4f477c), read on 2026-10-11. The repository is watched and re-audited when it changes.

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