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Example projects built on Coral, the query runtime for agents
https://withcoral.com/
- Python 81.7%
- Jupyter Notebook 9.9%
- Shell 6.7%
- Dockerfile 1.7%
| Filename | Latest commit message | Latest commit date |
|---|---|---|
Bumps python from 3.12-slim to 3.14-slim.
[](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)
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<!-- This is an auto-generated description by cubic. -->
---
## Summary by cubic
Update the SRE-agent Docker base image from `python:3.12-slim` to
`python:3.14-slim` to pick up security fixes and align with the latest
Python minor release.
<sup>Written for commit
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| .github | ||
| SRE-agent | ||
| .gitignore | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| LICENSE | ||
| README.md | ||
| SECURITY.md | ||
Coral Example Projects
Reference implementations for building production-style AI agents on top of Coral — a unified MCP layer over the observability, incident, code, and chat tools that real engineering teams already use.
These are full, runnable projects, not toy snippets. Fork them, point them at your own Coral instance and data sources, and adapt from there.
Projects
- SRE-agent — Slack bot that auto-investigates Datadog alerts end-to-end. Streams a live Block Kit "plan" of every Coral MCP tool call it makes, then posts a structured incident assessment with evidence pulled from Datadog, Sentry, and GitHub. Pydantic AI + Slack Bolt Socket Mode + Coral MCP over stdio. Deploys as a single-replica container.
License
Apache 2.0 — see LICENSE.