omega-router
Server Details
Route agent services by observed price and public usage evidence.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 2 tools
market_capabilities lists available capabilities, while route_service selects a provider based on metadata and policy. The two tools have clearly distinct actions and resources, leaving little room for confusion.
Both names use snake_case, but market_capabilities is a noun phrase while route_service follows a verb_noun pattern. This minor deviation is still readable and predictable.
With only two tools, the surface feels thin for a router service. A capability-listing tool and a routing tool cover the core but leave little room for auxiliary operations.
The domain likely requires inspecting provider metadata, managing buyer policies, or listing providers, but only capability listing and routing are present. Significant gaps will limit an agent's ability to fully administer or debug routing decisions.
Available Tools
2 toolsmarket_capabilitiesCInspect
List capabilities represented in the current snapshot.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does not state that this is a read-only operation, whether the snapshot is cached or live, how results are ordered or paginated, or what happens when no snapshot exists. "List" implies a read, but nothing is disclosed beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no wasted words. It is efficient, though its brevity borders on under-specification rather than genuine economy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no parameters, and no output schema, the description should define what a "capability" entry is and what the agent gets back. Neither is addressed, leaving the return content and the meaning of "current snapshot" unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there are no argument semantics to explain and the baseline of 4 applies. The description cannot add parameter meaning beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description has a verb ("List") and a resource ("capabilities"), so the action is identifiable. However, the core terms are undefined domain jargon: what a "capability" is and what constitutes the "current snapshot" are left entirely to inference. The sibling route_service is unrelated, so no differentiation is needed, but the purpose remains vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to call this tool, when not to, or what alternatives exist. The phrase "in the current snapshot" weakly implies reading live/current state, but this is inference rather than stated guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
route_serviceCInspect
Select a provider using observed public metadata and buyer policy.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | ||
| capability | Yes | ||
| max_price_usdc | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full behavioral burden. It mentions selection criteria (observed public metadata, buyer policy) but does not state whether the tool is read-only, what it returns, whether it incurs cost, or what side effects occur.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no wasted words. It is concise, though the brevity reflects under-specification rather than efficient completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the routing complexity, 0% schema description coverage, no annotations, and no output schema, the description is far too thin. It omits return behavior, selection mechanics, constraints, and parameter meaning that an agent needs to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no meaning to the three parameters. It never explains mode values (CHEAPEST, BALANCED, PROVEN, STRICT), capability values, or max_price_usdc, leaving the agent to infer entirely from names and enums.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a verb (Select) and resource (provider), but 'using observed public metadata and buyer policy' is abstract and does not clarify that routing is for a capability request. It also gives no sibling differentiation from market_capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus market_capabilities, nor any conditions or prerequisites. The description only says what it does, not when or why to choose it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
market_capabilities - First observed
route_service
Related MCP Connectors
Measured uptime, price and payment evidence for 19,021 agent services. Reliability, not quality.
Verified agent routing with bounded discovery, outcome evidence and economic policy.
Outcome-first agent fallback: free discovery, minimal routing, declared costs, verified execution.
Find and quote agent capabilities, then pay only the selected x402 execution URL.
Related MCP Servers
- FlicenseNot gradedqualityCmaintenanceEnables buyer-side spend-routing preflights before larger paid agent tool calls, with bounded planning and public-data evidence.-
- AlicenseAqualityFmaintenanceFind the most reliable AI agent for any task. Search 2,000+ agents across A2A and MCP with quality filters — min uptime, max latency, score thresholds. Check if an agent is alive before routing to it. Like Artificial Analysis, but for agent services.5MIT
- FlicenseNot gradedqualityDmaintenanceProvides real-time LLM pricing and availability data as an MCP server, enabling AI agents to make optimal model routing decisions at inference time with cited pricing sources.-
- FlicenseNot gradedqualityBmaintenanceProvides pre-fetch routing intelligence for AI agents by recommending the cheapest reliable route (HTTP, browser, machine endpoint, or avoid) before visiting a URL.-
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