Midpoint
midpointGeographic (great-circle) midpoint between two lat/lon points.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lat1 | Yes | ||
| lat2 | Yes | ||
| lon1 | Yes | ||
| lon2 | Yes |
midpointGeographic (great-circle) midpoint between two lat/lon points.
| Name | Required | Description | Default |
|---|---|---|---|
| lat1 | Yes | ||
| lat2 | Yes | ||
| lon1 | Yes | ||
| lon2 | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "lat1": 40.7128,
+ "lat2": 34.0522,
+ "lon1": -74.006,
+ "lon2": -118.2437
+ },
+ {
+ "lat1": 51.5074,
+ "lat2": 48.8566,
+ "lon1": -0.1278,
+ "lon2": 2.3522
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint, so the safety profile is clear. The description adds 'great-circle' method, but does not disclose edge cases or precision limits.
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?
Single sentence, no unnecessary words. Efficiently conveys the tool's purpose.
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?
The description is adequate for a simple tool with annotations and examples, but it lacks any mention of return value or error conditions. Since no output schema exists, this is a gap.
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 description coverage is 0%, and the description does not explain parameter meanings. While parameter names and examples are self-explanatory, there is no mention of valid ranges or units, leaving gaps.
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 clearly states the tool computes the geographic great-circle midpoint between two latitude/longitude points. This distinguishes it from sibling tools like centroid (multiple points) and bounding_box (bounds).
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?
No explicit guidance on when to use this tool versus alternatives. The name and description imply it's for exactly two points, but there's no comparison to centroid or other spatial 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 purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded are nearly identical; bet_research and polymarket_edges both analyze Polymarket markets). Descriptions are detailed but the sheer number of similar tools creates ambiguity for agents.
Most tools follow a verb_noun pattern (e.g., list_subscriptions, create_subscription), but a few use noun_verb (bet_research) or are standalone nouns (centroid, midpoint). Overall, the pattern is fairly consistent despite minor deviations.
35 tools is on the high side for an MCP server. The scope is broad (data access, prediction markets, geospatial, memory, subscriptions), so each tool earns its place, but the number is borderline for coherence.
The tool set covers a wide range of functionalities: data querying, entity profiles, comparisons, prediction market analysis, geospatial, memory, subscriptions, etc. Minor gaps exist (no batch operations or data export), but the core workflows are well-supported.