Custom Context MCP Server
Related Servers
Alternatives to Custom Context MCP Server
No user-submitted related servers found.
Related Servers
- -licenseBqualityNot gradedmaintenanceA Model Context Protocol server that enables AI models to extract structured data from websites through the extract\_structured\_data tool.121 npm-
- AlicenseNot gradedqualityDmaintenanceA server that implements the Model Context Protocol, providing a standardized way to connect AI models to different data sources and tools.10 npm11MIT
- AlicenseAqualityCmaintenanceA Model Context Protocol server that exposes AI workflow templates as callable tools, enabling MCP clients to list templates, inspect their input/output schemas, and execute them synchronously or asynchronously to get structured results.5MIT
- FlicenseAqualityDmaintenanceA Model Context Protocol server for querying large JSON files using JSONPath expressions, enabling LLMs to efficiently search and extract information from large JSON data.311-
- AlicenseCqualityFmaintenanceA Model Context Protocol server implementation that enables LLMs to query and manipulate JSON data using JSONPath syntax with extended operations for filtering, sorting, transforming, and aggregating data.236 npm90MIT
- FlicenseBqualityDmaintenanceA Model Context Protocol server that enables LLMs to extract and use content from unstructured documents across a wide variety of file formats.111-
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: group-text-by-json prepares text for grouping based on a JSON template, while text-to-json converts that grouped text into JSON. There is no overlap or ambiguity between them, as they represent sequential steps in a workflow.
Both tools follow a consistent verb-noun pattern with hyphens (group-text-by-json and text-to-json), clearly indicating their actions and targets. The naming is predictable and readable across the set.
With only 2 tools, the server feels thin for its apparent purpose of custom context management. This minimal set may limit functionality and require agents to work around gaps, as typical context-related operations might include more than just grouping and conversion.
The tool surface is severely incomplete for a custom context server. It lacks core operations such as creating, updating, deleting, or retrieving context entries, and only covers a narrow text-to-JSON conversion workflow, leaving significant gaps that will likely cause agent failures.