ecfr-mcp

find_recent_changes

Read-only

Find CFR sections amended after a specified date to track regulatory updates affecting acquisitions; returns identifiers, headings, and excerpts in recent-first order.

Instructions

Find CFR sections that have been modified since a given date.

Uses the search API with last_modified_on_or_after filter to find sections amended after the specified date. Returns section identifiers, headings, and excerpts, most recently amended first.

since_date must be in YYYY-MM-DD format. Results are capped at 10,000 by the API. Use title/chapter/part filters to narrow if needed.

Common pattern: find FAR changes since a specific date to check for regulatory updates that might affect ongoing acquisitions.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`part`	No
`title`	No
`chapter`	No
`per_page`	No
`since_date`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.0.7Aug 20, 2026

addedInput schema / properties / chapter / anyOf

Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]

addedInput schema / properties / part / anyOf

Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]

First observedv0.2.6May 16, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it uses the search API with a specific filter, returns results most recently amended first, and caps at 10,000 results. It also notes the date format requirement. This goes beyond the annotations without contradicting them.

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?

The description is well-structured: a clear first sentence stating the purpose, followed by mechanism details, parameter guidance, and a practical use case. Every sentence adds value, and the most important information (what it does) is front-loaded.

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?

The description is complete for an agent to call this tool correctly. It covers the purpose, the key parameter format, result ordering, result caps, and narrowing strategies. The output schema exists, so return values don't need to be described. The annotations cover safety. Nothing critical is missing.

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?

Schema description coverage is 0%, so the description must compensate. It explains the key parameter since_date (format YYYY-MM-DD) and mentions title/chapter/part filters for narrowing. It doesn't detail per_page, but the default of 100 is in the schema and the description's mention of the 10,000 cap provides context. This is strong compensation for a 0% coverage 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 the tool's purpose: finding CFR sections modified since a given date. It specifies the verb ('Find'), the resource ('CFR sections'), and the key constraint ('modified since a given date'). It also distinguishes itself from siblings like search_cfr by describing the specific use case and filter mechanism.

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 explains when to use this tool: to find recent changes to CFR sections, with a common pattern example (FAR changes). It also provides guidance on narrowing results with title/chapter/part filters and notes the 10,000 result cap, which helps the agent decide when to add filters.

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

Deploy Server