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sieve-mcp-server

sieve-mcp-server

Official

sieve_get_script

Reads the complete source of a Sieve mail filtering script so you can review and edit existing rules in place instead of replacing them, helping preserve current filters.

Instructions

Read the full source of a Sieve script. Always read the current script before changing it, and edit that text rather than writing a replacement from scratch, so existing rules are preserved.

Input Schema

NameRequiredDescriptionDefault
nameYesScript name exactly as listed by sieve_list_scripts (case-sensitive).
accountIdNoAccount id, as an alternative to accountName.
accountNameNoAccount name (from sieve_list_accounts). Optional when only one account is configured.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It makes the read-only nature implicit via 'Read' and adds useful workflow context, but says nothing about return format, error conditions if the script name is wrong, or account-resolution behavior. Adequate but with clear gaps for an un-annotated tool.

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

Conciseness5/5

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

Two sentences, front-loaded with the core purpose followed by actionable workflow guidance. Every sentence earns its place with no redundancy.

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?

Given three well-documented parameters, no annotations, and no output schema, the description covers what the tool does and how to use the result. It could be improved by noting what the return value looks like (full text, error if missing), but the essentials are present.

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

Parameters3/5

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

Schema coverage is 100%, with the 'name' parameter described as case-sensitive and tied to sieve_list_scripts, so the schema already does the semantic work. The description adds no meaning about parameters beyond what the schema provides, which is the baseline-3 case.

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?

States a specific verb ('Read') and resource ('the full source of a Sieve script'), making it clearly distinct from the write-oriented siblings like sieve_put_script and sieve_check_script. An agent can tell immediately this is a retrieval operation.

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

Usage Guidelines4/5

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

The description gives explicit workflow guidance ('Always read the current script before changing it, and edit that text rather than writing a replacement from scratch'), which tells the agent both when to call this tool and how to use the result. It does not name the specific alternative tool (e.g., sieve_put_script) or state exclusions, keeping it below a 5.

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