eos-mcp
MCP server for Arista EOS device operations via eAPI, enabling show commands, config push, and tech-support collection.
README
<!-- mcp-name: io.github.shigechika/eos-mcp -->
eos-mcp
MCP server for Arista EOS device operations via eAPI.
Exposes EOS show commands, running-config retrieval, configuration push (via configure session with commit timer), and tech-support collection to MCP-compatible AI assistants.
Installation
pip install eos-mcp
Configuration
Copy config.ini.example to ~/.config/eos-mcp/config.ini and fill in credentials:
[DEFAULT]
username = admin
password = yourpassword
transport = https
verify = false
[switch1.example.com]
tags = main,dc1
[switch2.example.com]
tags = main,dc1
Config file discovery order:
EOS_MCP_CONFIGenvironment variable./config.ini(current directory)~/.config/eos-mcp/config.ini
(Individual MCP tool calls may also override the path via a config_path
parameter.)
Usage
# Verify config and list devices
eos-mcp --check
# Test connectivity to a specific host
eos-mcp --check --check-host switch1.example.com
# Start MCP server (stdio transport)
eos-mcp
Tools
| Tool | Description |
|---|---|
health_check |
Report server version and config status (lightweight; does NOT connect to devices) |
get_router_list |
List registered devices (optional tag filter) |
get_device_facts |
Return structured facts for one device (model, serial, EOS version, uptime, memory) |
get_device_facts_batch |
Return device facts for multiple devices in parallel |
get_version |
Return EOS version string (quick connectivity check) |
run_command |
Run a single enable-mode command on one device |
run_commands |
Run multiple enable-mode commands on one device |
run_command_batch |
Run an enable-mode command on multiple devices in parallel |
run_commands_batch |
Run multiple enable-mode commands on multiple devices in parallel |
get_config |
Retrieve running-config |
get_config_diff |
Show config diff vs rollback checkpoint |
list_config_sessions |
List configure sessions and their state |
push_config |
Push config via configure session (dry_run=True by default) |
confirm_config_session |
Confirm a pending commit timer session |
abort_config_session |
Abort a pending session |
collect_tech_support |
Collect show tech-support output |
daily_brief |
Health check (environment, errdisabled, uptime, MLAG, recent syslog alerts) across multiple devices |
Development
Live smoke test
Unit tests check logic against fixtures; they cannot tell you that a tool has
stopped returning real data. scripts/smoke_test.py runs every registered
tool against the configured devices and fails on empty, malformed or error
answers:
# uses the same inventory file as the server (EOS_MCP_CONFIG)
uv run python scripts/smoke_test.py
uv run python scripts/smoke_test.py --only facts --traceback
- Read-only.
push_config,confirm_config_sessionandabort_config_sessionare skipped by name, and a test enforces that.collect_tech_supportis skipped too — it changes nothing, but it is minutes of device CPU for an answer no assertion would read. The command-running tools are exercised withshow version: they accept enable-mode commands in general, and a smoke test must not be the thing that types one that matters. - No payloads in the report. Tool names and statuses only; error text is redacted too, since every error here is prefixed with the device it came from and the payloads are configuration.
- Nothing estate-specific in the specs. The device the per-host tools need is discovered at run time from the configured inventory, and skipped when it is empty. Two tests keep it that way: one refuses those parameters as literals, the other bans anything address-shaped anywhere in the file, because this repository is public.
- Every probe refuses the
Error (<host>): ...line these tools return in place of raising — otherwise an unreachable device would read as a successful call. - CI enforces the cheap half: a tool registered without a probe spec fails the
build (
tests/test_smoke_probes.py), so adding a tool forces the question "how would we know it works?". scripts/smoke_harness.pyis the engine and holds no EOS knowledge: it is kept identical across the servers that share it, so fix engine bugs once and sync the file rather than patching this copy.
Requirements
- Python >= 3.10
- Arista EOS with eAPI enabled (
management api http-commands) - Network access to port 443 (HTTPS) on target devices
License
Apache-2.0
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。