nearest_postcodesFind nearby UK postcodes sorted by distance from a given postcode (e.g., 'SW1A 1AA'). Returns list with coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
| postcode | Yes | UK postcode to find neighbours for (e.g. "SW1A 1AA"). |
| Name | Required | Description | Default |
|---|---|---|---|
| results | Yes | Array of nearby postcodes sorted by distance |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "results": {
+ "description": "Array of nearby postcodes sorted by distance",
+ "items": {
+ "properties": {
+ "admin_district": {
+ "description": "Administrative district",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "admin_ward": {
+ "description": "Administrative ward",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "codes": {
+ "description": "Codes mapping object",
+ "type": "object"
+ },
+ "country": {
+ "description": "Country name",
+ "type": "string"
+ },
+ "eastings": {
+ "description": "Eastings grid reference",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "incode": {
+ "description": "Incode part of postcode",
+ "type": "string"
+ },
+ "lat": {
+ "description": "Latitude coordinate",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "lon": {
+ "description": "Longitude coordinate",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "northings": {
+ "description": "Northings grid reference",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "outcode": {
+ "description": "Outcode part of postcode",
+ "type": "string"
+ },
+ "parliamentary_constituency": {
+ "description": "Parliamentary constituency",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "postcode": {
+ "description": "The UK postcode",
+ "type": "string"
+ },
+ "region": {
+ "description": "Region name",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "required": [
+ "postcode",
+ "incode",
+ "outcode",
+ "country",
+ "codes"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "results"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "postcode": "SW1A 1AA"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation read-only, non-destructive, and idempotent. The description adds useful behavioral details beyond annotations, such as sorting by distance and returning coordinates, which helps set expectations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence, front-loaded with the main purpose ('Find nearby UK postcodes'), followed by the sorting and output details. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter, an output schema, and rich annotations, the description is completely adequate. It specifies the input, the sorting behavior, and the return shape, leaving no critical gaps for an agent to misuse the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the single 'postcode' parameter fully described. The description only repeats the example and adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Find') with a clear resource ('nearby UK postcodes') and distinguishing behavior (sorted by distance from a given postcode). This clearly separates it from sibling tools like lookup_postcode, random_postcode, and validate_postcode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool: when you need nearby postcodes for a given postcode. It does not explicitly mention alternatives or exclusion cases, but the context is clear enough for an agent to select it over related sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping responsibilities: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all serve similar lookup purposes. entity_profile, compare_entities, and recent_changes all retrieve company data. Several Polymarket tools overlap in edge detection. The large number of tools with fuzzy boundaries makes it difficult for an agent to select the correct one.
Tool names are a mix of conventions: some use verb_noun (lookup_postcode, validate_postcode, resolve_entity), others are verb_phrase (ask_pipeworx, deep_research, suggest_questions), and a few are compound (polymarket_arbitrage, scan_competitor_ai_presence). No uniform pattern, though the structure is readable.
Despite being named 'postcodes', only 4 of 35 tools are directly about postcodes. The vast majority belong to a broad data platform (Pipeworx) with specialized tools for finance, betting, news, etc. The count is excessive for a focused service, and many tools are only useful for users of that platform, leading to clutter.
For a postcode server, the tools cover basic needs (lookup, nearest, random, validate). However, the server's actual scope is much larger; within that broader scope, there are notable gaps: no general text search, no direct access to raw SEC filings, and many tools depend on paid plans or external accounts. The coverage is uneven and incomplete for a unified data platform.