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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
UNFRAGILE_API_KEYNoAPI key for higher rate limits
UNFRAGILE_API_URLNoAPI base URLhttps://unfragile.ai

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
searchA

Search the Unfragile match graph for AI tools, frameworks, APIs, MCP servers, agents, and more. Returns ranked results with capability matches and graph signals. Every query feeds the graph.

find_mcpsA

Find MCP servers by capability need. Use this when you need to discover MCP servers for specific integrations (e.g., databases, APIs, cloud services). Returns MCP servers ranked by capability match.

get_artifactA

Get full details and capabilities for a specific AI artifact by name or slug. Uses search-based lookup (best-effort name matching — may return a different artifact for ambiguous names like 'express'). Use this to understand what an artifact can do before adding it to your stack.

resolve_capabilityA

Resolve a capability:// URI or natural-language capability into ranked AI artifacts. This is Unfragile's capability DNS primitive. Use when an agent knows what capability it needs and must choose the safest current artifact at runtime.

trust_passportA

Get the machine-readable trust passport for an AI artifact. Use this before an agent selects a tool, API, MCP server, model, repo, or framework for a task. Returns capability URIs, permissions, data access risk, known failure modes, observed outcomes, and trust score.

compareA

Compare two AI artifacts side-by-side. Shows capabilities, pricing, rank, and graph signals for each. Uses search-based lookup (best-effort name matching). Use this when deciding between alternatives.

find_stackB

Assemble a complete AI harness stack for a use case. Given a description of what you're building, returns recommended tools across harness layers: orchestration, tools/MCPs, memory, guardrails, context assembly, and evaluation. This is the key differentiator — Unfragile understands that modern AI systems are composed of 5-15 tools working together.

feedbackA

Report whether a recommended tool worked or not. This closes the learning loop — the Unfragile graph uses this feedback to improve future recommendations. Call this after trying a tool from search results.

subscribeA

Set up a persistent watch for new AI tools matching a query. Get notified daily when something new appears in the Unfragile graph. Requires at least one notification channel (email or webhook).

unsubscribeA

Cancel a persistent watch (monitor). Use the monitor ID returned from subscribe.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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