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Glama

Ebird

by io.github.pipeworx-io

Recent Observations

recent_observations
Read-onlyIdempotent

Recent bird sightings in a region. region_code is the eBird identifier — countries are 2-letter ("US", "GB"), states "US-CA", counties "US-CA-075", and birding hotspots use the "L" code from eBird (e.g., "L99381"). Optionally filter to one species.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
backNoDays back (1-30, default 14)
max_resultsNo1-10000 (default 100)
region_codeYeseBird region code
species_codeNoOptional eBird species code (use find_species to look up)
include_provisionalNoInclude unconfirmed observations (default false)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of observations returned
region_codeYeseBird region code used for the query
observationsYesList of bird observations

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "region_code": "US-CA"
+  },
+  {
+    "back": 7,
+    "include_provisional": true,
+    "max_results": 50,
+    "region_code": "L99381",
+    "species_code": "norbob"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of observations returned",
+      "type": "number"
+    },
+    "observations": {
+      "description": "List of bird observations",
+      "items": {
+        "properties": {
+          "checklist_id": {
+            "description": "eBird checklist submission ID",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "common_name": {
+            "description": "Common name of the species",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "count": {
+            "description": "Number of birds observed",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "exotic_category": {
+            "description": "Exotic status category if applicable",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "latitude": {
+            "description": "Latitude of observation",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "location": {
+            "description": "Location name",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "location_id": {
+            "description": "eBird location identifier",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "longitude": {
+            "description": "Longitude of observation",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "observed_at": {
+            "description": "ISO datetime of observation",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "private_location": {
+            "description": "Whether location is private",
+            "type": [
+              "boolean",
+              "null"
+            ]
+          },
+          "reviewed": {
+            "description": "Whether observation was reviewed",
+            "type": [
+              "boolean",
+              "null"
+            ]
+          },
+          "scientific_name": {
+            "description": "Scientific name of the species",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "species_code": {
+            "description": "eBird species code",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "valid": {
+            "description": "Whether observation passed validation",
+            "type": [
+              "boolean",
+              "null"
+            ]
+          }
+        },
+        "required": [],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "region_code": {
+      "description": "eBird region code used for the query",
+      "type": "string"
+    }
+  },
+  "required": [
+    "region_code",
+    "count",
+    "observations"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, making the safety profile clear. The description adds format details but does not disclose additional behavioral traits beyond what annotations and schema provide.

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 concise, front-loaded with the main purpose, and uses a single paragraph efficiently. It covers essential details without unnecessary repetition.

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

Completeness4/5

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

Given the tool has an output schema, the description focuses on input parameters and usage context. It explains the region code format thoroughly and notes optional filtering, making it fairly complete for its complexity.

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 coverage is 100%, but the description adds significant value by explaining the region_code format with examples and mentioning species_code lookup via find_species. This goes beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns recent bird sightings in a region, with a specific verb and resource. It explains the region code format but does not differentiate from sibling tools like nearby_observations or recent_notable.

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

Usage Guidelines3/5

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

The description provides context on when to use (recent sightings by region) and explains region code format and optional species filter. However, it lacks explicit guidance on when not to use or alternatives among sibling tools.

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

All Ebird toolsInspect
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TDQS

A3.6/5.0
Disambiguation3/5

Several tools are close cousins: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same underlying data catalog, and bet_research/polymarket_edges/polymarket_arbitrage share a betting-research niche. The eBird tools are clearly a different cluster, but the server carries so many unrelated domains that an agent may struggle to pick the right category member (e.g., stable router vs beta router vs grounded router).

Naming Consistency3/5

Almost everything is snake_case, but the pattern is not uniform: there are plenty of verb_noun names (find_species, list_subregions, scan_competitor_ai_presence) mixed with bare consumer-style names (ask_pipeworx, bet_research, entity_profile, deep_research) and short helpers (recall, forget, remember). No mixed scripting-case chaos, but no consistent verb_noun or noun_verb system either.

Tool Count2/5

36 tools is heavy for a server that calls itself Ebird: only ~5 tools actually relate to bird observation, while the rest span Pipeworx data lookups, Polymarket betting, legal/regulatory analyzers, memory, subscriptions, competency scanning, npm package checking, and llms.txt generation. The count would be reasonable for a broad data platform, but the server's stated identity and the bundled tool set do not match, making the scope feel bloated and incoherent.

Completeness2/5

For a bird-centric server, the surface is thin: you can find a species, list subregions, and pull recent/notable observations, but you cannot get coordinated eBird atlases, hotspot details, species life-history stats, or region-based species lists. For the larger set of unrelated tools, completeness is impossible to gauge about a missing domain; the eBird purpose feels unfinished even though the miscellaneous tools are overloaded.

Resources