Skip to main content
Glama

Server Details

AgentBridge is the only MCP server that gives AI agents access to structured China knowledge assets—university reports, industry briefings, policy analysis, and real-time web content—through x402 micropayments on Base. Everything is machine-readable, pay-per-use, and settled in USDC.

Ownership verified
Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

C2.9/5.0

Scored across 4 tools

Disambiguation4/5

Each tool has a distinct purpose: status check, asset retrieval, web page fetching, and asset search. Minor potential overlap between fetch_asset and search_assets is clarified by descriptions.

Naming Consistency3/5

Mixed naming conventions: agentbridge_status uses a prefix with underscore, while others use verb_noun. Still readable but not fully consistent.

Tool Count3/5

Only 4 tools for a server that bridges knowledge assets and web content feels somewhat thin; additional operations like payment initialization or asset filtering might be expected.

Completeness3/5

Covers basic asset fetch/search and web page fetching, but lacks clear operations for payment processing despite fetch_asset mentioning a payment endpoint. Also no write or update capabilities, limiting full lifecycle coverage.

Available Tools

4 tools
agentbridge_statusAgentbridge StatusCInspect

AgentBridge MCP status

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.5/5.0
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 and discloses nothing. It doesn't state whether this is a read-only probe, whether it requires auth, or what the check reports. 'Status' weakly implies a read-only health check, but no behavioral trait is actually described.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a four-word fragment with no waste, but it is under-specified rather than concise; there is no front-loaded purpose statement to speak of since it merely echoes the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with an output schema and no annotations, the description is minimal but the complexity is low. It still fails to say what 'status' actually reports, which an agent would want before calling it in preference to the fetch/search siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so per the rubric the baseline is 4. The description adds no parameter meaning, but none is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

"AgentBridge MCP status" essentially restates the tool name and title with no added verb+resource specificity. It does not clarify what 'status' means (health, connectivity, version, uptime) or distinguish it from the sibling fetch/search tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to call this versus alternatives. A status check's usage is weakly implied, but no context, triggers, or exclusions are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

fetch_assetFetch AssetCInspect

Retrieve AgentBridge knowledge asset metadata and payment endpoint.

ParametersJSON Schema
NameRequiredDescriptionDefault
asset_idYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

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. It never states whether this is read-only, whether authentication or payment is required to hit the 'payment endpoint', whether access is rate-limited, or whether it fails on unknown IDs. 'Retrieve' weakly implies a read, but nothing substantive is disclosed.

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?

A single, front-loaded sentence with no filler. It is efficient, though it is arguably too terse for what it needs to convey.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described. However, for a tool with an undocumented required parameter, no annotations, and an unusual 'payment endpoint' aspect, the description leaves real gaps around input sourcing and access requirements.

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 single parameter is required, so the schema supplies no meaning. The description says nothing about what an asset_id looks like or where to obtain one (presumably from search_assets), leaving the caller without the info needed to invoke the tool.

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 gives a specific verb ('Retrieve') and resource ('AgentBridge knowledge asset metadata and payment endpoint'), so an agent can tell it apart from search_assets and fetch_web_page. It does not explicitly name its siblings, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is given, and the obvious alternative (search_assets, for discovery before fetching) is never mentioned. The agent must infer that an asset_id is already known.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

fetch_web_pageFetch Web PageBInspect

Fetch webpage content and convert it to clean Markdown.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.1/5.0
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. It discloses the output format (Markdown) but says nothing about permissions, rate limits, handling of JS-heavy pages, redirects, or errors. For a network-fetching tool with zero annotation coverage, this is thin.

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?

Single front-loaded sentence, zero waste. Every word earns its place and the action is immediately clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists, so return-value explanation isn't required. However, with no annotations and no parameter documentation, the description leaves significant behavioral gaps (auth, limits, error handling) unaddressed for a network tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but there is only one parameter (url) whose meaning is obvious from its name and the tool's purpose. Baseline for very low parameter counts is 4; the description adds nothing about URL format, redirects, or scheme restrictions, so a 3 is fair.

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?

States a specific verb (Fetch) and resource (webpage content), and adds the transformation detail (convert to clean Markdown), which distinguishes it from siblings like fetch_asset. It doesn't explicitly name or contrast with siblings, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this vs. fetch_asset or search_assets, no mention of prerequisites (network access, URL requirements), and no exclusions. The agent must infer usage entirely from the name and one sentence.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_assetsSearch AssetsCInspect

Search available AgentBridge knowledge assets.

ParametersJSON Schema
NameRequiredDescriptionDefault
keywordNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.7/5.0
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 behavioral burden, yet it discloses nothing about matching behavior, whether an empty keyword returns everything, pagination, rate limits, or result counts. Only the presence of an output schema saves it from being fully opaque.

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?

It is a single front-loaded sentence with no filler or redundancy. The terseness is a size problem rather than a conciseness problem, since the sentence itself wastes nothing.

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?

An output schema exists, so return values need not be explained, but for a search tool with an undocumented keyword parameter and zero annotations, an agent lacks the information needed to call it correctly versus fetch_asset. The definition is too thin for the tool's role.

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 single parameter 'keyword' has a default of empty string, which is semantically important (does empty mean match-all?). The description adds no meaning about what keyword matches against or what the default implies, so it fails to compensate for the coverage 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 gives a specific verb (Search) and resource (AgentBridge knowledge assets), so the purpose is clear. However, it offers no differentiation from the sibling fetch_asset, which also retrieves assets, so an agent cannot tell them apart from the description alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to search versus when to use fetch_asset, agentbridge_status, or fetch_web_page. The agent is left to infer that 'search' is for discovery, but nothing states this, nor are prerequisites or exclusions given.

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.

  1. 4 tool updates
    • First observedagentbridge_status
    • First observedfetch_asset
    • First observedfetch_web_page
    • First observedsearch_assets

Related MCP Connectors

Related MCP Servers

  • F
    license
    Not graded
    quality
    D
    maintenance
    56 pay-per-call MCP endpoints for AI agents. Market signals, macro economics, crypto/DeFi, geopolitical intelligence, SEC filings, GitHub velocity, sanctions screening. USDC on Base Mainnet via x402.
    -
  • A
    license
    A
    quality
    C
    maintenance
    Market intelligence MCP server enabling AI agents to buy crypto sentiment reads, divergence verdicts, and analyst answers via pay-per-call x402 micropayments on Base.
    6
    70 npm
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources