io.github.shigechika/junos-mcp

collect_rsi_batch

Gather RSI/SCF diagnostic data from multiple Junos devices concurrently. Select targets by hostnames or tags, control parallel workers, and save outputs to a directory.

Instructions

Collect RSI/SCF from multiple devices in parallel.

Uses ThreadPoolExecutor for concurrent collection. Default 20 workers matches junos-ops CLI default for RSI collection. Either hostnames or tags selects the targets; if both are omitted, every router in config.ini is targeted. When both are given, the intersection is used.

Args: hostnames: List of target device hostnames tags: Tag filter. Each list element is one tag group (comma-separated tags AND together within a group); multiple list elements OR together across groups. Combined with hostnames the result is the intersection. output_dir: Directory to save output files (empty uses config RSI_DIR or current dir) max_workers: Maximum parallel threads (default 20) config_path: Path to config.ini (empty string uses default search)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "collect_rsi_batch"
  }
}

Input Schema

Name	Required	Description	Default
`tags`	No
`hostnames`	No
`output_dir`	No
`config_path`	No
`max_workers`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.16.2Jul 28, 2026
Removedv0.16.1Jul 27, 2026
First observedv0.1.0May 26, 2026

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses concurrency, default workers, and target intersection logic, but no annotation support and omits potential side effects or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-organized with summary, details, and parameter list, though slightly verbose; every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers essential aspects for a batch collection tool with 5 params and no annotations, though could mention error handling or output file details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Explains each parameter in detail despite 0% schema coverage, including complex tag filter logic and default behaviors, adding significant value beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it collects RSI/SCF from multiple devices in parallel using ThreadPoolExecutor, distinguishing it from singular collect_rsi and batch command tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes target selection via hostnames/tags and defaults, but lacks explicit when-to-use vs alternatives like singular collect_rsi.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.