A
license-
qualityB
maintenanceEnables AI agents to perform web searches with full content retrieval and multi-engine provenance, including trust scoring and local corpus persistence, via MCP integration.
1
2
Apache 2.0
World Resolver
Server Details
Resolve real-world capability gaps: validate native MCPs, search the web, and record unmet demand.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
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MCP client
Glama
MCP server
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
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Tool Definition Quality
B3.4/5.0
Tool DescriptionsB
Average 3.2/5 across 3 of 3 tools scored.
Server CoherenceA
Disambiguation5/5
Each tool serves a clearly distinct function: resolve performs the search/validation, submit_mandate records intent for future fulfillment, and report_outcome provides feedback on resolver performance. No two tools appear to overlap in purpose.
Naming Consistency4/5
Two tools follow the verb_noun pattern (report_outcome, submit_mandate), while 'resolve' is a lone verb. All names use lowercase and underscores, so the style is consistent, but the missing noun in 'resolve' is a minor deviation.
Tool Count4/5
Three tools is slightly on the lean side for a service that claims to handle real-world capability requests, but the set covers the core actions of resolve, submit, and report. It is within the reasonable range and each tool earns its place.
Completeness4/5
The tools form a coherent loop for capability resolution and feedback. A minor gap is the lack of a way to query outstanding mandates or inspect historical outcomes, but the core workflow appears complete for its stated purpose.
Available Tools
3 toolsreport_outcomeCInspect
Report whether a resolver request actually worked and how much agent friction it required.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| success | Yes | ||
| latencyMs | No | ||
| requestId | Yes | ||
| agentSteps | No | ||
| failureReason | No | ||
| selectedServer | No |
Tool Definition Quality
C2.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the reporting purpose and does not disclose side effects, persistence, idempotency, prerequisites, or return behavior. 'Report' suggests a write/telemetry operation, but the description does not clarify the tool's actual behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that starts with the core action ('Report') and communicates the two key dimensions (success and friction). It is concise and readable, but the brevity sacrifices detail needed in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and six parameters with zero schema descriptions, the description is too thin. It does not explain the relationship to sibling tools, what values to provide beyond requestId/success, or what the tool does with the data. This telemetry/reporting tool needs more behavioral context for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
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 parameter-specific meaning. It mentions 'agent friction' generally, which could loosely map to agentSteps or latencyMs, but no parameter is named or explained. With six undocumented parameters, the description fails to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Report') and clearly identifies the object ('a resolver request'), stating exactly what is reported (success and friction). It distinguishes itself from siblings like resolve and submit_mandate by focusing on post-request outcome reporting, though it does not explicitly name those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after a resolver request, providing some contextual guidance. However, it does not explicitly state when to use this tool versus alternatives like resolve or submit_mandate, nor does it mention any exclusions. This is implied usage, not explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
resolveBInspect
Resolve a real-world capability request. Search the official MCP Registry, actively validate public candidate MCP tool surfaces, then fall back to live web search when native coverage is weak or absent. Weak Registry matches never suppress capability-gap telemetry.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | What the principal agent wants done | |
| budget | No | ||
| currency | No | ||
| deadline | No | ||
| location | No | ||
| telemetry | No | aggregate_only | |
| categoryHint | No |
Tool Definition Quality
B3.1/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the transparency burden. It discloses the search-and-fallback strategy and the telemetry behavior for weak Registry matches, but omits side effects, return values, or error paths. These omissions prevent a higher score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences that front-load the purpose, then detail the method, and end with a behavioral caveat. It is economical and avoids filler, though a more structured format could improve scannability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters and no output schema, the description is too high-level. It doesn't explain how parameters influence resolution, what the return format is, or what constitutes a successful result, leaving significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 14%, with only 'task' described. The description adds no explanation for budget, currency, deadline, location, telemetry, or categoryHint, leaving their semantics entirely to the schema. It fails to compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves a real-world capability request and outlines the resolution process (registry search, validation, web fallback), which distinguishes it from siblings. However, it doesn't explicitly contrast with report_outcome or submit_mandate, so it doesn't reach the top tier.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for capability requests and mentions a fallback condition (weak/absent native coverage), but it doesn't explicitly say when to use this tool over siblings or provide exclusions/prerequisites. Usage guidance is present but implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_mandateAInspect
Record high-intent demand for a capability an agent wants fulfilled. Supplier contact and spending are not enabled yet.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | ||
| currency | No | ||
| deadline | No | ||
| location | No | ||
| authority | No | get_quotes | |
| maxBudget | No | ||
| telemetry | No | aggregate_only | |
| categoryHint | No |
Tool Definition Quality
A3.7/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It mentions that supplier contact and spending are not enabled yet, which is a useful limitation, but it does not detail write behavior, authentication, or side effects, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action, and free of redundant information. It achieves clarity with minimal words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 8 parameters, no output schema, and no annotations, yet the description is only two sentences. It lacks details on return values, parameter relationships, and mandate lifecycle, making it under-specified for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explicit parameter explanations. It only implies 'task' as the capability but fails to clarify currency, deadline, authority, maxBudget, telemetry, and other fields, leaving users to infer from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool records high-intent demand, using a specific verb ('Record') and resource ('capability'). It distinguishes from sibling tools by focusing on demand capture rather than outcome reporting or resolving.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for high-intent demand with a clear context, but it does not explicitly name alternatives or provide exclusions. However, the action is distinct from siblings, providing clear contextual differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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