streamparse-mcp
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| parse_partial_jsonA | Parse a JSON string that may be truncated mid-stream (e.g. a partial LLM tool call). Always returns a valid JSON value with synthetic closure of any open strings, arrays, or objects. Reports whether the input represented a complete top-level value, plus the cursor path where parsing stopped. |
| extract_json_from_textA | Extract and parse a JSON value embedded in messy LLM output. Strips ```json fences, leading/trailing prose, code comments, and tolerates other LLM-isms. Returns the first parseable value and where in the text it started. |
| validate_jsonA | Strict-mode RFC 8259 validator. Returns ok=true and the parsed value if the input is valid JSON; otherwise returns ok=false with a precise byte position and human-readable message. |
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 3 tools
Each tool targets a distinct JSON scenario: partial/truncated input, embedded in LLM text, and strict validation. No overlap in purpose.
All tools follow a consistent verb_noun pattern (parse_partial_json, extract_json_from_text, validate_json), making the set predictable.
Three tools is well-scoped for a focused JSON parsing and validation server—each tool serves a clear need without excess or deficiency.
The surface covers the key JSON handling tasks: parsing partial streams, extracting from messy text, and strict validation. No obvious gaps given the domain.