@mrrlin-dev/external-agents
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| pingA | Ping the server |
| list_agentsA | List configured agents merged with their current state |
| get_stateA | Return the current external-agents state file (per-agent healthy/not_installed/needs_auth/quota_exhausted/errored_transient with metadata) |
| probe_agentB | Probe a specific agent by id; runs an install-check and updates the state file. Returns the new state. |
| set_credentialA | Persist an API-key env variable so the next dispatch (and future sessions) see it. Writes to ~/.local/state/external-agents/keys.env (mode 0600). |
| pick_agentsA | Pick up to N distinct healthy candidates by round-robin (preference_order + last_used_at). Optional min_distinct_providers enforces cross-provider diversity. ROUTING NOTE: default filter is tier='weak' — that is intentional. Most atomic tasks (single-file edits, refactors, glue code, summaries, format conversions, well-scoped fixes) get the same quality answer from a weak-tier free-tier model as from Claude Opus or Codex Pro, in a fraction of the time and cost. Reach for strong-tier (filter tier='strong') ONLY when the task actually needs deep reasoning: multi-step debugging, architecture decisions, ambiguous requirements, novel algorithms. Frontier ≠ better output for the long tail of routine work; often it is slower with no quality gain. Be smart, not lavish. |
| dispatchA | Run a specific agent by id with a prompt. transport ('generate' | 'cli') overrides the default (generate preferred when entry declares it). escalate_to_pro=true uses the same-provider strong-tier entry instead. ROUTING NOTE: for the same task, weak-tier free-tier models (Gemini flash, Groq llama, DeepSeek, OpenRouter :free) are usually correct AND fast enough. Use dispatch against Claude Opus, Codex Pro, or any strong-tier subscription model ONLY when the task genuinely needs frontier capability. escalate_to_pro is a retry lever, not a default. If a weak agent's output is wrong, first ask whether the SPEC was ambiguous (fix the spec, re-dispatch weak) before escalating tier — reaching for stronger models hides prompt-engineering failures behind expensive compute. |
| get_statsA | Aggregate dispatch telemetry from ~/.local/state/external-agents/dispatch-log.jsonl. Returns per-agent counts, tokens, outcomes; per-transport totals. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/mrrlin-dev/external-agents'
If you have feedback or need assistance with the MCP directory API, please join our Discord server