Bridge A2A agents to MCP tool format.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_name | No | A2A agent name to map |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / a2a_taskRemoved value: -{
- "description": "JSON string of the A2A task object. Must include at minimum a 'message' field with 'parts'. Example: '{\"id\": \"task-1\", \"message\": {\"role\": \"user\", \"parts\": [{\"type\": \"text\", \"text\": \"Check provider status\"}]}}'",
- "title": "A2A Task",
- "type": "string"
-}Input schema / properties / agent_nameAdded value: +{
+ "default": "",
+ "description": "A2A agent name to map",
+ "title": "Agent Name",
+ "type": "string"
+}Input schema / properties / target_mcp_server_urlRemoved value: -{
- "default": "https://mcp.thinkneo.ai/mcp",
- "description": "URL of the target MCP server endpoint (e.g. 'https://mcp.thinkneo.ai/mcp'). Defaults to ThinkNEO's own MCP server.",
- "title": "Target Mcp Server Url",
- "type": "string"
-}Input schema / requiredRemoved value: -[
- "a2a_task"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description need not repeat those. However, it adds no behavioral context: it does not explain what 'bridging' entails, what happens to the agent, whether a mapping is created, or what the output represents. The description is too vague to be informative beyond the annotations.
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 extremely short, but under-specification is not the same as conciseness. A single vague phrase 'Bridge A2A agents to MCP tool format' lacks structural elements and does not earn its place as a useful definition; it would benefit from at least one more sentence explaining the action.
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?
Despite having annotations, an output schema, and a single parameter, the description is fundamentally incomplete. It does not explain what the tool actually does, when to use it, or how it relates to the sibling bridge tools. With such an ambiguous action, the agent cannot reliably select or invoke this tool 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 100% for the single parameter (agent_name: 'A2A agent name to map'), so the schema already provides necessary semantics. The description adds no extra meaning about how the parameter is used, but the baseline of 3 is appropriate given complete schema coverage.
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 identifies the tool as bridging A2A agents to MCP tool format, giving a specific verb and direction. However, 'bridge' is ambiguous—it could mean convert, map, list, or expose—and it does not distinguish from sibling bridge tools like thinkneo_bridge_generate_agent_card or thinkneo_bridge_mcp_to_a2a.
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?
No guidance is provided on when to use this tool versus the many alternative bridge tools. There are no context clues, prerequisites, or examples of appropriate scenarios, leaving the agent to guess based solely on the name.
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.