mcp-drone-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MCP_DRONE_SSH_CA_KEY | No | SSH CA private key used to sign drone host certificates during enrollment. | |
| MCP_DRONE_ENROLL_TOKEN | No | Token used for authenticated host enrollment of drones. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tasks | {} |
| tools | {
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| fleet_snapshotC | Get drones, capacity, and task state. |
| register_droneC | Register or heartbeat a drone. ssh_user may name the SSH account or config alias user. |
| run_jobsC | Submit and, by default, dispatch one-shot or long-lived jobs as a batch. |
| stage_bundleB | Copy a local script or directory to one drone once for reuse by many jobs. |
| task_statusC | Read one task. |
| task_logsC | Read bounded task logs. |
| task_artifactsC | List task artifact metadata. |
| fetch_artifactC | Fetch one verified artifact to the coordinator host. |
| cancel_taskB | Cancel a queued or running task. |
| dispatch_pendingB | Dispatch queued tasks to connected drones. |
| reconcile_runningB | Reconcile running task state with connected drones. |
| promote_persistentC | Move a drone onto an already-mounted persistent data volume. |
| user_eventC | Record a dashboard/user action for an agent. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 13 tools
Most tools target clearly distinct resources or actions (task_status vs task_logs vs task_artifacts, fetch_artifact vs task_artifacts). The one soft overlap is run_jobs, which 'submits and by default dispatches' jobs, versus dispatch_pending and reconcile_running, which also manage task dispatch state, creating some ambiguity about when to use each. Otherwise boundaries are clean.
All names use snake_case consistently. Action tools follow verb_noun (register_drone, cancel_task, dispatch_pending, fetch_artifact) while read tools use noun_noun (task_status, task_logs, task_artifacts, fleet_snapshot), which is a readable convention but not a single uniform pattern.
13 tools sits well within the ideal range and each maps to a real facet of drone orchestration (fleet state, registration, job submission, staging, task inspection, artifact handling, dispatch/reconcile). No obvious filler or redundancy in the count.
The surface covers a full task lifecycle: register, stage, submit, dispatch, monitor, fetch artifacts, cancel, reconcile, and promote persistence. Minor gaps exist, such as no explicit drone deregistration/removal or bulk task listing, but core workflows have no dead ends.