Bridge MCP tool registry to A2A format. Shows tool-to-skill mappings.
| Name | Required | Description | Default |
|---|---|---|---|
| tool_name | No | MCP tool name to bridge |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / argumentsRemoved value: -{
- "default": "{}",
- "description": "JSON string of arguments to pass to the MCP tool (e.g. '{\"workspace\": \"prod\", \"period\": \"this-month\"}')",
- "title": "Arguments",
- "type": "string"
-}Input schema / properties / mcp_tool_nameRemoved value: -{
- "description": "Name of the MCP tool to bridge (e.g. 'thinkneo_check_spend')",
- "title": "Mcp Tool Name",
- "type": "string"
-}Input schema / properties / target_a2a_agent_urlRemoved value: -{
- "default": "https://agent.thinkneo.ai/a2a",
- "description": "URL of the target A2A agent endpoint (e.g. 'https://agent.thinkneo.ai/a2a'). Defaults to ThinkNEO's own A2A agent.",
- "title": "Target A2A Agent Url",
- "type": "string"
-}Input schema / properties / tool_nameAdded value: +{
+ "default": "",
+ "description": "MCP tool name to bridge",
+ "title": "Tool Name",
+ "type": "string"
+}Input schema / requiredRemoved value: -[
- "mcp_tool_name"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true and destructiveHint=false, so the safe, non-mutating nature is covered. The description adds that it shows tool-to-skill mappings, but does not explain behavior such as whether a missing tool_name means 'all tools' or what the output structure looks like. Since the output schema exists, some return details are offloaded, but behavioral specifics are still thin.
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 consists of two short sentences that are front-loaded with the verb 'Bridge'. There is no filler or redundant information, and every word contributes meaning.
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 tool's simplicity (one optional parameter, read-only annotations, and an output schema), the description is mostly adequate. However, it fails to position this tool against the closely related siblings thinkneo_bridge_a2a_to_mcp and thinkneo_bridge_list_mappings, and it does not explain the effect of the optional tool_name parameter. This leaves gaps in understanding when and how to invoke it.
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 input schema covers 100% of the single parameter (tool_name) with a description 'MCP tool name to bridge', so the baseline is 3. The tool description does not add extra meaning beyond the schema, such as clarifying that the parameter is optional or how an empty value is interpreted. It does not compensate for any missing schema detail because none is missing.
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 uses a specific verb ('bridge') and identifies the resource ('MCP tool registry') and target format ('A2A format'), also stating it shows tool-to-skill mappings. This makes the core purpose clear. However, it does not explicitly distinguish itself from the sibling tool thinkneo_bridge_list_mappings, which likely performs a similar listing function.
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?
The description provides no guidance on when to use this tool versus alternatives. With siblings like thinkneo_bridge_a2a_to_mcp (reverse direction) and thinkneo_bridge_list_mappings, an agent receives no help selecting among them. The usage context is only implied, not stated with exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as the multiple safety-check tools (thinkneo_check, thinkneo_detect_injection, thinkneo_evaluate_guardrail) and the many cost/reporting tools (thinkneo_agent_roi, thinkneo_decision_cost, thinkneo_business_impact). An agent would struggle to reliably pick the correct tool for a given intent. The boundaries between dashboard, audit, and reporting tools are particularly fuzzy.
All tools share the thinkneo_ prefix, but the remaining naming is inconsistent: some follow verb_noun (check_spend, list_alerts), some use noun_verb (compliance_generate, alert_rule_create), and others are bare nouns (business_impact, cache_status). This mix makes it hard to predict tool names based on action and object.
With 68 tools, this is an extremely large surface area, far beyond the typical 3-15 well-scoped set and even beyond the 25+ heavy threshold. Even for a comprehensive enterprise platform, the sheer number overwhelms an agent's ability to choose effectively. It feels like a kitchen-sink approach rather than a curated toolkit.
The toolset covers a wide range of governance, observability, and cost-management features, but there are notable lifecycle gaps: SLAs can be defined but not updated or deleted, alert rules lack an update operation, and registry entries have no remove/unpublish. Also, policy management is limited to checking, with no create/update tool. The memory tools feel out of place and lack a delete operation.