sciple-mcp 0.3.1

MCP server for populating and managing Sciple platform content

Sciple Platform MCP Server

MCP server that lets a local Claude populate and manage Sciple platform content — environments, services, observability dashboards, and runbooks — via the Sciple REST API. Engineers use it to bootstrap tenant structure, maintain the service catalog, build dashboards, and author runbooks without leaving their AI coding session.

Published on PyPI: https://pypi.org/project/sciple-mcp/ Source: https://github.com/navaganeshr/sciple-mcp

Install

The recommended install is via uv — it's a one-time setup that gives you uvx, which fetches and caches sciple-mcp on demand. No clone required.

# Install uv (one-time, only if you don't have it)
curl -LsSf https://astral.sh/uv/install.sh | sh

uvx sciple-mcp will resolve the latest version from PyPI on first run and cache it locally.

Configuration

The server reads three environment variables:

SCIPLE_API_URL=http://localhost:8000/api/v1
SCIPLE_API_TOKEN=sciple_pat_...
SCIPLE_TENANT_ID=<your tenant id>

SCIPLE_API_TOKEN is a personal access token minted under Profile → Access tokens in the Sciple dashboard, scoped to the permissions the server should have:

Domain	Permissions
Environments	environments.view, environments.manage
Services	services.view, services.manage
Observability	observability.view, observability.manage
Runbooks	observability.view, observability.manage (runbooks live under the observability permission family)

The PAT is single-tenant — its bound tenant must equal SCIPLE_TENANT_ID. Calls against a different tenant return 403.

Wire into Claude Desktop / Claude Code

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (Claude Desktop) or your Claude Code MCP config:

{
  "mcpServers": {
    "sciple-platform": {
      "command": "uvx",
      "args": ["sciple-mcp"],
      "env": {
        "SCIPLE_API_URL": "http://localhost:8000/api/v1",
        "SCIPLE_API_TOKEN": "sciple_pat_...",
        "SCIPLE_TENANT_ID": "..."
      }
    }
  }
}

Then restart Claude. You should see 26 platform tools available.

The Sciple dashboard also renders this exact JSON block — with SCIPLE_API_URL and SCIPLE_TENANT_ID pre-filled from the running environment — inside the "How to use this token with Claude" panel on Profile → Access tokens. Generate a token there and copy the snippet directly.

Tools

Environments

Tool	Description
list_environments	List all environments in the tenant (id, name, slug, group, default flag)
create_environment	Create an environment with optional group assignment and default flag
update_environment	Update an environment's name, description, group, or sort order
delete_environment	Delete an environment by id (irreversible)
list_environment_groups	List environment groups (id, name, slug, AWS account binding)
create_environment_group	Create an environment group with optional AWS account binding

Services

Tool	Description
list_services	List all services in the tenant catalog (id, name, slug)
create_service	Create a service in the catalog with kind, language, SCM provider, and repository
update_service	Update a service's metadata, lifecycle, owner, tags, links, or environment associations
delete_service	Delete a service from the catalog by id (irreversible)

Observability

Tool	Description
list_dashboards	List all observability dashboards in the tenant (id, name, panel count)
get_dashboard	Get a dashboard's name, description, and panel list
create_dashboard	Create a new dashboard with optional description
update_dashboard	Replace a dashboard's name and description (full PUT; name required)
delete_dashboard	Delete a dashboard and all its panels (irreversible)
add_panel	Add a panel to a dashboard with an optional PromQL or CloudWatch Metrics query (mutually exclusive). Bind the panel to a specific data source with datasource_id (recommended for CloudWatch — without it the panel may render empty). Log panels (logs/log_table) are accepted and can be bound to a data source, but log-query content (index, query, group-by) still has to be set in the UI.
delete_panel	Delete a panel from a dashboard (irreversible)

Runbooks

Tool	Description
list_runbooks	List all runbooks in the tenant with lifecycle status and cell count
get_runbook	Get a runbook with its cells (name, status, content preview per cell)
create_runbook	Create a new runbook in draft status
add_cell	Add a markdown / shell / http cell to a runbook with optional k8s/ecs/ec2 target
update_cell	Update a cell's content or execution target
delete_cell	Remove a cell from a runbook
reorder_cells	Set the execution order of all cells in a runbook
promote_runbook	Advance the runbook lifecycle: draft → reviewed → standard
deprecate_runbook	Mark a runbook as deprecated

Runbook lifecycle: draft → reviewed → standard. Deprecation is one-way from any state.

Security

The server can only do what the PAT's scope allows. Attempts to write without the relevant manage permission return a 403 from the API and are surfaced as an error in Claude's response. The PAT is revocable at any time from Profile → Access tokens in the Sciple dashboard — revoking it immediately cuts off the server's access without any config change.

Development

To work on the server itself:

git clone https://github.com/navaganeshr/sciple-mcp
cd sciple-mcp
uv sync --all-groups
uv run python -m pytest -q

Releases are tag-driven via a GitHub Actions workflow using PyPI Trusted Publishing (OIDC). To cut a release:

1. Bump version in pyproject.toml.
2. Commit, then git tag vX.Y.Z && git push origin vX.Y.Z.
3. Approve the pypi environment deployment in the Actions UI.