legion-ai-intelligence
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_ai_incidentsB | Search classified AI agent security incidents. Types: api_exploit, sandbox_escape, prompt_injection, unauthorized_action, agent_escape, data_exfiltration. Severities: critical, high, medium, low. |
| get_incident_statsB | Get total AI security incident counts by type and severity. |
| get_ai_model_pricingC | Get current pricing for AI models. Providers: openai, anthropic, google, mistral, groq, cohere, together. |
| get_gpu_pricingC | Get current GPU cloud pricing. Providers: lambdalabs, runpod, vastai, coreweave, together, modal, replicate. |
| get_ai_routeB | Get AI model routing recommendation based on live status, pricing and drift. Priorities: cheap, fast, reliable, balanced. |
| get_ai_statusA | Check which AI providers are currently online/offline with latency. |
| get_model_driftC | Check AI model behavioral drift observations. |
| get_ai_jobsC | Search AI industry job postings. |
| get_ai_regulationsC | Search AI regulations and policy documents. |
| get_company_intelligenceC | Cross-signal intelligence: incidents + jobs + funding per AI company. |
| scan_n8nB | Scan a self-hosted n8n instance for CVE-2026-21858 vulnerability. |
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 11 tools
Most tools target clearly distinct signals: pricing, status, drift, jobs, regulations, incidents, and routing. The only mild overlap is get_incident_stats (aggregate counts) vs get_ai_incidents (searchable records), but the descriptions clearly separate counting from searching. get_company_intelligence is a synthesis tool and doesn't collide with the atomic tools.
Ten of eleven tools follow a clean get_* snake_case pattern (get_ai_model_pricing, get_gpu_pricing, get_ai_route, etc.). scan_n8n breaks the get_ prefix convention, but it is an action verb appropriate to a scan operation, so the deviation is minor and readable.
Eleven tools is well-scoped for an AI-ecosystem intelligence server, with each tool covering a distinct signal source (pricing, status, drift, incidents, jobs, regulations, routing, vulnerability scanning). No obvious filler or redundancy.
The surface covers a broad range of intelligence signals plus a cross-signal aggregator (get_company_intelligence) and a routing recommender, giving good lifecycle coverage. Minor gaps exist, such as no historical/trend query for pricing or status, but core workflows are covered.