Free platform to test MCP clients without installing anything. Create mock tools with dynamic templates, configurable delays, conditions (if/then), and response sequences. Supports JSON-RPC 2.0 over Streamable HTTP. Built-in text_echo and json_echo tools. Rate-limited tiers: anonymous (5 calls/min, 1 mock tool), registered (10 calls/min, 4 mock tools), premium (60 calls/min, unlimited). Zero setup — no install, no registration required. More info: https://www.testmcp.dev
Scored across 2 tools
The two tools are clearly differentiated by input type (JSON vs. plain text), so an agent can select based on the data format. However, they execute essentially the same echo operation, which introduces mild ambiguity for mixed or uncertain inputs.
Both tools follow a consistent verb_noun pattern (json_echo, text_echo), using lowercase with underscores. The naming is predictable and uniform.
With only 2 tools, the server sits at the low end of the acceptable range. For a simple echo service, this is reasonable, but it feels thin compared to the typical 3-15 tool scope.
The server covers the two most common echo formats (JSON and plain text), but lacks a generic echo or additional formats (e.g., XML, binary). Minor gaps exist, but the core purpose is addressed.
Receives JSON and returns it as echo (max 256 chars serialized for Free tier, up to 100kb for Premium).
| Name | Required | Description | Default |
|---|---|---|---|
| json_data | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description effectively discloses the echo behavior and size constraints. It is clear that the tool is read-only and returns the input. A slightly higher score would require explicit mention of no side effects or authentication needs.
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 sentence that is efficient and front-loaded with the core purpose. Every word is necessary, and there is no redundant information.
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?
For a simple echo tool with one parameter, the description covers purpose and size limits. It does not explain what 'echo' means in detail, but given the presence of an output schema, that is acceptable. Minor improvement could clarify the echo behavior.
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 description does not reference the only parameter, json_data. With 0% schema description coverage, the description should provide additional context but fails to do so. The parameter name is self-explanatory, but the description adds no semantic value.
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 clearly states the tool receives JSON and returns it as echo, identifying the core purpose. However, it lacks an explicit statement that it is a testing/debugging tool, and sibling differentiation is implied rather than explicit.
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 size limits for Free vs Premium tiers, which gives context, but does not explicitly guide when to use json_echo over text_echo. The differentiation is implied by the input type.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Receives plain text (max 256 chars for Free tier, up to 100kb for Premium) and returns it as echo.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
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 clearly states that the tool echoes back the input text and discloses character limits by tier. This covers key behavioral traits such as input size constraints and nondestructive echo behavior, though it could mention if it’s idempotent or has other side effects.
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 sentence, front-loaded with the tool’s purpose, and every part is necessary. No wasted words.
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 has an output schema (not shown but true), the description does not need to explain return values. It covers input constraints (size limits) and the basic echo behavior, which is sufficient for such a simple tool. The tool's low complexity and presence of output schema make this description complete.
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%, so the description must compensate. It implies the 'text' parameter by mentioning 'plain text' and adds meaning with size limits. However, it does not explicitly define the parameter name or type beyond what the schema provides. This adds some value but not full compensation.
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 clearly states that the tool receives plain text and returns it as an echo. This distinguishes it from the sibling tool 'json_echo', which presumably handles JSON input. The verb 'returns' and the specific resource 'text echo' are well-defined.
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 tier-based size limits (256 chars for Free, 100kb for Premium), offering context on when the tool can be used. However, it does not explicitly state when to prefer this tool over 'json_echo' or provide exclusion guidance. The absence of explicit 'when-not-to-use' notes keeps it from a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
json_echotext_echo
Add one secure layer between your agents and this server.
