CiscoDevNet/thousandeyes-mcp-community
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Model Context Protocol (MCP) server for Cisco ThousandEyes v7 enables AI assistants to query various network monitoring and performance data.
thousandeyes-mcp
Model Context Protocol (MCP) server for Cisco ThousandEyes v7 — lets AI assistants query tests, agents, alerts, dashboards, widgets, and test results (network, page-load, web-transactions, path-vis).
Community project - NOT affiliated with Cisco/ThousandEyes.
Status: Alpha (MVP) read-only.
Why (business value)
-
Faster troubleshooting: Ask AI to “show outages in the last hour” or “figure out where the network traffic is getting stuck at” for super fast issues identification.
-
Consistency over scripts: Standard MCP tools replace one-off curl snippets.
-
Safer by default: Read-only; token is only read from env.
-
Composable workflows: Chain tools (tests → dashboard → widget → test results).
Current capabilities
Tool | What it does | Endpoint(s) |
---|---|---|
te_list_tests(aid?, name_contains?, test_type?) | Lists tests (filter by name/type/AG) | GET /v7/tests |
te_list_agents(agent_types?, aid?) | Lists enterprise / enterprise-cluster / cloud agents | GET /v7/agents |
te_get_test_results(test_id, test_type, window?/start?/end?/aid?/agent_id?) | Test results (e.g., network , page-load , web-transactions ; not dns-server ) | GET /v7/test-results/{testId}/{testType} |
te_get_path_vis(test_id, window?/start?/end?/aid?/agent_id?/direction?) | Path visualization data | GET /v7/test-results/{testId}/path-vis |
te_list_dashboards(aid?, title_contains?) | Lists dashboards | GET /v7/dashboards |
te_get_dashboard(dashboard_id, aid?) | Dashboard details incl. widget list | GET /v7/dashboards/{dashboardId} |
te_get_dashboard_widget(dashboard_id, widget_id, window?/start?/end?/aid?) | Widget data for a dashboard | GET /v7/dashboards/{dashboardId}/widgets/{widgetId} |
te_get_users() | Lists users in the ThousandEyes account | GET /v7/users |
te_get_account_groups() | Lists account groups available to the authenticated org | GET /v7/account-groups |
Requirements
- Python 3.12+
- ThousandEyes API v7 bearer token in env:
TE_TOKEN
Install
python3 -m pip install -r requirements.txt
# If Python is externally managed:
# python3 -m venv .venv && . .venv/bin/activate && pip install -r requirements.txt
Configure (Claude Desktop)
Add to your claude_desktop_config.json
(or Dev UI):
{
"mcpServers": {
"thousandeyes": {
"command": "/ABS/PATH/TO/python3",
"args": ["/ABS/PATH/TO/repo/src/server.py"],
"env": { "TE_TOKEN": "YOUR_OAUTH_BEARER_TOKEN" }
}
}
}
Token is read only from env, never written to disk.
Try it out!
Example 1: In-depth Analysis of Customer Journeys for Optimizing Performance
https://github.com/user-attachments/assets/5915fb97-20ef-42af-ad53-f6889a839330
Example 2: Visualizing Performance Data
https://github.com/user-attachments/assets/c5ef796a-42fc-422f-82c0-9f8c4c68aeb8
Here are some other prompts to try out
- What was the network health of the Patient Portal between 13:00–14:00 CET on 1 Sep 2025?
- Which regions/agents showed elevated page-load time for the Patient Portal between 08:00–10:00 UTC today?”
- Show uptime and TTFB for the Patient Portal homepage over the last 24 hours, and call out any drops.
- Which enterprise agents had >1% packet loss to api.patient-portal.example.com this morning?”
- Open the Patient Portal dashboard and list the widgets relevant to availability and the login flow and callout any widgets reporting no data
- For test
, compare network latency during 10:00–10:30 UTC vs. the prior 30 minutes.” - Show path visualization anomalies for test
around 15:30 UTC yesterday.”
Security & privacy
- Read-only tools - no writes.
- No tokens or org data stored - token only via
TE_TOKEN
. - Respect org rate limits - backoff on the roadmap.
Roadmap
- Adding feature support for alerts, tags, event detection, endpoint agents, etc.
- Optional retries/backoff on 429.
- Minimal CI and examples catalog.
License & attribution
- Apache-2.0
- “ThousandEyes” is a trademark of Cisco Systems, Inc. This project is NOT affiliated with Cisco/ThousandEyes.
Maintainers
- Aditya Chellam · Kiran Kabdal