LegalAIMCP Directory

Recommend legal AI tools for a firm

recommend_legal_ai_tools

Read-onlyIdempotent

Rank legal AI tools by fit for a specific practice area and firm size, with a score and the matched factors behind it. Use this instead of search_legal_ai_tools when someone describes their firm (e.g. "solo family law practice" or "20-attorney litigation firm") and wants a recommendation, not just a list.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of recommendations to return (1-5, default 5)
`firm_size`	Yes	Firm size: solo, small (2-10 attorneys), mid (11-50), or large (50+)
`practice_area`	Yes	Practice-area category slug — get slugs from list_legal_ai_categories

Output Schema

TableJSON Schema

Name	Required	Description	Default
`count`	Yes	Number of recommendations returned
`recommendations`	Yes	Ranked highest-fit first. Empty when nothing in the directory matched either input.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedAug 30, 2026

addedOutput schema / properties / recommendations / items / properties / pricing_note

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "description": "Informational only, never affects rank: paid/contact tiers often bundle dedicated support that a free/freemium pick may not. Ties are broken by cost alone — this lets the requester weigh support separately."
+}

changedOutput schema / properties / recommendations / items / required

Previous value: -[
-  "slug",
-  "name",
-  "tagline",
-  "category",
-  "category_label",
-  "pricing_model",
-  "pricing_details",
-  "links_verified",
-  "links_verified_at",
-  "website",
-  "repo",
-  "install_command",
-  "maker",
-  "listing_url",
-  "score",
-  "matched_factors"
-]New value: +[
+  "slug",
+  "name",
+  "tagline",
+  "category",
+  "category_label",
+  "pricing_model",
+  "pricing_details",
+  "links_verified",
+  "links_verified_at",
+  "website",
+  "repo",
+  "install_command",
+  "maker",
+  "listing_url",
+  "score",
+  "matched_factors",
+  "pricing_note"
+]

AddedAug 30, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds behavioral value beyond those annotations by stating that the tool ranks tools and returns 'a score and the matched factors behind it,' and by framing it as recommendation-oriented rather than list-oriented. No contradictions with annotations.

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, no filler. The first sentence front-loads the core behavior and output; the second sentence provides actionable usage guidance. Every clause contributes to selection or invocation.

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?

With an output schema present, a fully described input schema, and annotations covering safety and idempotency, the description completes the picture by clarifying when to choose this tool over its sibling. Nothing needed for correct selection or invocation is missing.

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 description coverage is 100%, and each parameter already has clear semantics, including enum values and defaults for limit. The description reinforces the role of practice area and firm size in determining fit but does not need to add more; the schema carries the parameter documentation burden.

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 opens with the specific verb 'Rank' and names the resource ('legal AI tools') and the ranking criteria ('fit for a specific practice area and firm size'), and promises a score plus matched factors. It clearly distinguishes itself from the sibling search_legal_ai_tools by saying it gives a recommendation rather than just a list.

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?

The description explicitly says 'Use this instead of search_legal_ai_tools' and identifies the exact triggering condition: when someone describes their firm and wants a recommendation, not just a list. Concrete examples ('solo family law practice', '20-attorney litigation firm') make the usage boundary easy for an agent to apply.

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

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