Edge Delta MCP Server

The Edge Delta MCP Server is a Model Context Protocol (MCP) server that provides seamless integration with Edge Delta APIs, enabling advanced automation and interaction capabilities for developers and tools.

Use Cases

• Extract and analyse observability data from Edge Delta.
• Build AI‑powered tools and applications that interact with Edge Delta’s platform.

Pipeline Configuration Tools

The server exposes tools to inspect and change Edge Delta pipelines. Write operations follow a safe loop: validate → save → deploy, with rollback.

Tool	What it does
get_pipelines / get_pipeline_config / get_pipeline_history	Discover pipelines and read their config and version history.
validate_pipeline_config	Validate a config YAML without saving it. Returns {valid, reason}.
save_pipeline_config	Save the full config YAML as a new version (does not deploy).
deploy_pipeline	Deploy a saved version to the fleet.
revert_pipeline	Roll back to a previously saved version.
add_pipeline_source	Add a data source node to a pipeline.

Typical edit flow: get_pipeline_config → edit YAML → validate_pipeline_config → save_pipeline_config → get_pipeline_history → deploy_pipeline (revert_pipeline to roll back).

Live-capture tools

Validating that a config is valid is not the same as confirming a change actually transformed the data. The live-capture tools sample real before/after data flowing through pipeline nodes on running agents, so an agent can verify a transformation took effect.

Tool	What it does
start_pipeline_capture	Start a capture task on a pipeline (duration, optional node list, max items).
get_pipeline_capture_status	Poll per-agent status for a capture task.
get_pipeline_capture_results	Fetch captured before/after samples per node.
get_pipeline_capture_task	Show the currently active capture task, if any.

Capture flow: start_pipeline_capture → get_pipeline_capture_status (poll until an agent reports success) → get_pipeline_capture_results (compare each node's before vs after to confirm the transformation).

Processor dry-run (test) tools

Develop and verify a processor against sample logs offline — no save, no deploy, no live traffic. The offline complement to live-capture: capture proves what did happen, this proves what will happen.

Tool	What it does
test_pipeline_ottl	Dry-run OTTL statements against sample OTEL log items; returns the transformed items.
test_pipeline_node	Dry-run a full processor node of any type (log_to_metric, log_to_pattern, extract_metric, parse_json_attributes, grok, mask, …); returns the items it emits per output path.

Iterate until the output is right, then add the statements/node to the pipeline, save_pipeline_config → deploy_pipeline, and confirm on live data with the capture tools. Use test_pipeline_ottl for OTTL transforms (its ExtractPatterns also covers regex field extraction); use test_pipeline_node for non-OTTL node types such as log-to-metric and log-to-pattern.

Prerequisites

1. Docker Engine ≥ 20.10 installed and running.
2. Docker Buildx plug‑in available:
   • macOS / Windows – included with Docker Desktop.
   • Debian / Ubuntu

     sudo apt-get update && sudo apt-get install -y docker-buildx-plugin
     

   • Fedora / RHEL / CentOS

     sudo dnf install -y docker-buildx-plugin   # or yum install …
     

   • Other distros (manual fallback)

     mkdir -p ~/.docker/cli-plugins
     curl -sSL \
       https://github.com/docker/buildx/releases/latest/download/buildx-$(uname -s | tr '[:upper:]' '[:lower:]')-amd64 \
       -o ~/.docker/cli-plugins/docker-buildx
     chmod +x ~/.docker/cli-plugins/docker-buildx
     

3. An Edge Delta API token with the required scope – create one here.
4. Your Edge Delta organisation ID – find it here.

Build (container image)

First‑time setup (creates a multi‑platform builder and boots it):

docker buildx create --name edgedelta-builder --use
docker buildx inspect --bootstrap

Build the image and load it into the local Docker daemon:

docker buildx build --load -t mcp/edgedelta .

ℹ️ The --load flag streams the image back to your local Docker engine so you can run it directly with docker run mcp/edgedelta ….

Installation

Usage with Cursor

{
  "mcpServers": {
    "edgedelta": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e ED_ORG_ID",
        "-e ED_API_TOKEN",
        "ghcr.io/edgedelta/edgedelta-mcp-server:latest"
      ],
      "env": {
        "ED_API_TOKEN": "<YOUR_TOKEN>",
        "ED_ORG_ID": "<YOUR_ORG_ID>"
      }
    }
  }
}

Library Usage

The exported Go API of this module is experimental and may change without notice. If you rely on it in production, please open an issue describing your use case so we can stabilise the relevant surface.

License

Licensed under the terms of the MIT licence. See LICENSE for full details.