MCP server for GitHub Actions intelligence: workflow performance, config audit, and billing analysis
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
claude mcp add gha-intel-mcp -- npx -y @barissozudogru/gha-intel-mcp{
"mcpServers": {
"gha-intel-mcp": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "<github_token>"
}
}
}
}GITHUB_TOKENMCP Servers overview
<img src="./assets/banner-gha-intel.svg" alt="gha-intel-mcp" width="888" />
An MCP server for GitHub Actions workflow timing analysis, configuration auditing, and billing insights.
## Tools
| Tool | Description |
|------|-------------|
| `list_workflow_performance` | Computes average, min, max, and p95 duration statistics for recent workflow runs. |
| `analyze_workflow_config` | Evaluates workflow YAML for caching, parallelism, concurrency, artifacts, checkout depth, timeouts, runner pinning, Docker caching, and triggers. |
| `get_billing_usage` | Returns Actions billing minutes and estimated cost by runner type, plus per-repo cache utilisation. |
## Requirements
- Node.js >= 18 (uses native `fetch`)
- A GitHub personal access token with `repo` and `read:org` scopes
## Setup
Three transport modes are available. Choose whichever fits your deployment:
---
### Option A: stdio (local, recommended for desktop clients)
The server runs as a subprocess of the MCP client over stdin/stdout. No network port required.
#### Claude Desktop
`~/Library/Application Support/Claude/claude_desktop_config.json` (macOS)
`%APPDATA%\Claude\claude_desktop_config.json` (Windows)
```json
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
```
#### Claude Code
```bash
claude mcp add gha-intel -e GITHUB_TOKEN=ghp_your_token -- npx -y @barissozudogru/gha-intel-mcp
```
#### Cursor
`~/.cursor/mcp.json`
```json
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
```
#### Windsurf
`~/.codeium/windsurf/mcp_config.json`
```json
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
```
#### VS Code + Copilot
`.vscode/mcp.json` (workspace) or user settings
```json
{
"servers": {
"gha-intel": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
```
#### Cline
Open Cline settings, navigate to MCP Servers, and add:
```json
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
```
#### Continue.dev
`~/.continue/config.yaml`
```yaml
mcpServers:
- name: gha-intel
command: npx
args:
- -y
- "@barissozudogru/gha-intel-mcp"
env:
GITHUB_TOKEN: ghp_your_token
```
#### Zed
`~/.config/zed/settings.json`
```json
{
"context_servers": {
"gha-intel": {
"command": {
"path": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
}
```
#### JetBrains (IntelliJ, PyCharm, WebStorm, etc.)
Go to **Settings > Tools > AI Assistant > MCP** and add:
```json
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
```
---
### Option B: HTTP (remote or cloud clients)
Start the server in HTTP mode and point clients at the endpoint:
```bash
GITHUB_TOKEN=ghp_your_token npx @barissozudogru/gha-intel-mcp --http
# Server listens on http://0.0.0.0:3000/mcp
# Health check: http://localhost:3000/health
```
Or set via environment variable instead of the flag:
```bash
TRANSPORT=http PORT=3000 GITHUB_TOKEN=ghp_your_token npx @barissozudogru/gha-intel-mcp
```
#### Cursor (HTTP)
`~/.cursor/mcp.json`
```json
{
"mcpServers": {
"gha-intel": {
"url": "http://localhost:3000/mcp"
}
}
}
```
#### VS Code + Copilot (HTTP)
`.vscode/mcp.json`
```json
{
"servers": {
"gha-intel": {
"type": "http",
"url": "http://localhost:3000/mcp"
}
}
}
```
#### Windsurf (HTTP)
`~/.codeium/windsurf/mcp_config.json`
```json
{
"mcpServers": {
"gha-intel": {
"serverUrl": "http://localhost:3000/mcp"
}
}
}
```
#### Continue.dev (HTTP)
`~/.continue/config.yaml`
```yaml
mcpServers:
- name: gha-intel
url: http://localhost:3000/mcp
```
---
### Option C: Docker
```bash
docker build -t gha-intel-mcp .
docker run -p 3000:3000 -e GITHUB_TOKEN=ghp_your_token gha-intel-mcp
```
The container starts in HTTP mode by default. Point your client at `http://localhost:3000/mcp`.
---
## Tool Reference
### list_workflow_performance
Fetch real run timing data and compute job-level statistics.
| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `owner` | string | yes | GitHub owner (user or org) |
| `repo` | string | yes | Repository name |
| `workflow_id` | string | yes | Workflow file name (e.g. `ci.yml`) or numeric ID |
| `count` | number | no | Number of recent runs to analyse (default: 10, max: 100) |
**Output:** Per-job and per-step timing stats (avg, min, max, p95), overall run timing, and a list of recent run conclusions.
---
### analyze_workflow_config
Parse and audit a workflow YAML for optimisation opportunities.
| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `workflow_content` | string | yes | Full YAML content of the workflow file |
**Output:** Findings grouped by severity (critical / warning / info / good) across nine categories, each with a concrete recommendation.
**Categories analysed:** Dependency caching, matrix strategy and fail-fast, concurrency groups and cancel-in-progress, artifact uploads, git checkout depth, job timeout-minutes, runner version pinning, Docker layer caching, and trigger path filters.
---
### get_billing_usage
Retrieve billing and cache consumption data.
| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `owner` | string | yes | GitHub username or organisation |
| `repo` | string | no | Repository name for repo-scoped cache and run stats |
**Output:** Total minutes used, plan utilisation, estimated cost broken down by runner type (Ubuntu / macOS / Windows / large runners), plus per-repo cache size and utilisation percentage.
---
## Environment Variables
| Variable | Required | Description |
|----------|----------|-------------|
| `GITHUB_TOKEN` | yes | GitHub personal access token. Requires `repo` scope for private repos, `read:org` for org billing. |
| `TRANSPORT` | no | Set to `http` to enable HTTP mode (default: stdio). |
| `PORT` | no | HTTP port when running in HTTP mode (default: `3000`). |
## License
MIT
What people ask about gha-intel-mcp
What is barissozudogru/gha-intel-mcp?
+
barissozudogru/gha-intel-mcp is mcp servers for the Claude AI ecosystem. MCP server for GitHub Actions intelligence: workflow performance, config audit, and billing analysis It has 2 GitHub stars and its last recorded update is dated 2026-08-20.
How do I install gha-intel-mcp?
+
You can install gha-intel-mcp by cloning the repository (https://github.com/barissozudogru/gha-intel-mcp) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is barissozudogru/gha-intel-mcp safe to use?
+
Our security agent has analyzed barissozudogru/gha-intel-mcp and assigned a Trust Score of 95/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains barissozudogru/gha-intel-mcp?
+
barissozudogru/gha-intel-mcp is maintained by barissozudogru. The last recorded GitHub activity is dated 2026-08-20, with 0 open issues.
Are there alternatives to gha-intel-mcp?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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