MCP Server Boilerplate
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| json_readA | Read and analyze JSON. Always use this tool to explore JSON structure, understand data schema, or get high-level overviews of large JSON. Use this for initial data exploration or when you need to understand the shape and types of data before extracting specific values. |
| json_extractA | Extract specific data using paths, filters, patterns, or slices from JSON files. Always use this tool when you need to retrieve particular values, filter arrays/objects by conditions, search for patterns, or slice data. Ideal for targeted data extraction, data transformation, and focused analysis of specific JSON elements. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes with no overlap. json_extract is for targeted data extraction and transformation, while json_read is for initial exploration and schema understanding. The descriptions explicitly guide when to use each tool, eliminating any ambiguity.
Both tools follow a consistent verb_noun pattern with 'json_' prefix and descriptive actions (extract, read). The naming is perfectly uniform and predictable across the tool set.
With only 2 tools, the server feels too thin for a general-purpose JSON handling domain. While the tools are well-defined, a complete JSON manipulation surface would typically include additional operations like validation, transformation, or writing capabilities. The count is insufficient for comprehensive JSON workflows.
There are significant gaps in the JSON manipulation surface. The server only provides read/extract capabilities with no tools for creating, updating, validating, or writing JSON data. This creates dead ends for agents needing to modify or generate JSON, making it incomplete for common JSON-related tasks.