Skip to main content
Glama

kolmo-mcp-server

by io.kolmo.www

Permit jurisdiction coverage

list_permit_jurisdictions
Read-onlyIdempotent

List the jurisdictions in Kolmo's permit catalog (King, Pierce, Snohomish counties). Compact by default — results is keyed by county (King / Pierce / Snohomish), each a list of {slug, name, verified} — the whole catalogue in one call (~4K tokens), enough to pick a jurisdictionSlug for estimate_permit_fee, check_permit_requirements or get_permit_rule_details. Pass slug for one jurisdiction's full record (department, fee-schedule URL, phone, code cycles, notes), or detail: true for full records on every row.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoOne jurisdiction by slug, e.g. "bellevue" or "mercer-island". Returns its full record.
countyNoFilter by county
detailNoIf true, every row carries the full record. Default false (compact rows). The full catalogue in detail is ~9x larger — prefer `slug` when you need one city.
verifiedOnlyNoIf true, only return rows where portal_url is populated (verified from official source). Default false.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
detailYes
resultsNo
attributionYes

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses meaningful behavior: compact default output shape, results keyed by county, full-record fields for slug/detail modes, approximate token size, and the ~9x size penalty for detailed output. This helps an agent predict response cost and shape.

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?

The description is dense and front-loaded with purpose, then output shape, then parameter modes. It is efficient overall, though the county list appears twice ('(King, Pierce, Snohomish counties)' and '(King / Pierce / Snohomish)'), a minor redundancy.

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

Completeness5/5

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

Given the annotations, detailed input schema, and presence of an output schema, the description supplies everything an agent needs to choose and invoke the tool correctly: default behavior, response keying, parameter effects, size expectations, and downstream usage examples.

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

Parameters4/5

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

The input schema already documents all four parameters thoroughly, so the baseline is 3. The description adds value by clarifying compact vs. full-record output implications, token estimates, and the practical guidance to prefer `slug` over `detail: true`, slightly exceeding schema-only semantics.

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 uses a specific verb and resource: 'List the jurisdictions in Kolmo's permit catalog' with explicit county scope. It also distinguishes the tool from sibling permit tools by explaining its output is meant for choosing a jurisdictionSlug for estimate_permit_fee, check_permit_requirements, or get_permit_rule_details.

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

Usage Guidelines5/5

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

It gives clear when-to-use guidance: use the compact catalogue to select a jurisdictionSlug for downstream permit tools, and prefer the `slug` parameter when only one jurisdiction is needed because full detail is ~9x larger. This explicitly routes an agent to the right mode and related tools.

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

All kolmo-mcp-server toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Several permit-related tools have overlapping boundaries: answer_permit_question, check_permit_requirements, and get_permit_rule_details all return timeline/fee/submittal information and can answer 'do I need a permit' style questions. get_material_catalog and get_material_options also target similar material-selection needs. The descriptions help, but an agent could easily select the wrong tool in the permit cluster.

Naming Consistency5/5

All 36 tools follow a consistent snake_case verb_noun pattern, with get_ for single-item lookups and list_ for collection queries. There are no camelCase or mixed-style exceptions, so the naming is predictable and scannable.

Tool Count2/5

36 tools is well above the 25+ threshold and feels heavy even for a multi-domain construction assistant. Several retrieval tools overlap (list_services/list_projects/list_blog_posts vs search_content, get_material_catalog vs get_material_options), suggesting consolidation opportunities.

Completeness4/5

The permit workflow is well covered from parcel lookup through requirements, fees, submittals, and data freshness, and the prospect journey has services, estimates, financing, weather, reviews, and contact submission. Minor gaps exist, such as no active permit-status lookup and no way to create/update content, but these are outside the apparent read-only/lead-gen scope.

Resources