Teardrop

Web Search

web_search

Read-only

Real-time web search via Tavily. Use for current events, fact-checking, and research. Set search_depth='advanced' for complex research queries (higher quality, higher cost). Set topic='news' for recent headlines or 'finance' for market information.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	Search query
`topic`	No	Search topic: 'general' for web, 'news' for headlines, 'finance' for markets	general
`num_results`	No	Number of web search results to return (1–20, default 5).
`search_depth`	No	'basic' for fast results, 'advanced' for thorough research (higher cost)	basic

Output Schema

TableJSON Schema

Name	Required	Description	Default
`note`	No
`query`	Yes
`results`	Yes
`num_results`	Yes

Schema Changelog

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

Changed12 schema fields changedAug 14, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```
addedInput schema / properties / num_results / title
```
Added value: +"Num Results"
```
addedInput schema / properties / query / title
```
Added value: +"Query"
```
addedInput schema / properties / search_depth / title
```
Added value: +"Search Depth"
```
addedInput schema / properties / topic / title
```
Added value: +"Topic"
```
addedInput schema / title
```
Added value: +"mcp_web_searchArguments"
```

addedOutput schema / $defs

Added value: +{
+  "SearchResult": {
+    "properties": {
+      "score": {
+        "anyOf": [
+          {
+            "type": "number"
+          },
+          {
+            "type": "null"
+          }
+        ],
+        "default": null,
+        "title": "Score"
+      },
+      "snippet": {
+        "title": "Snippet",
+        "type": "string"
+      },
+      "title": {
+        "title": "Title",
+        "type": "string"
+      },
+      "url": {
+        "title": "Url",
+        "type": "string"
+      }
+    },
+    "required": [
+      "title",
+      "url",
+      "snippet"
+    ],
+    "title": "SearchResult",
+    "type": "object"
+  }
+}

addedOutput schema / properties / results / items / $ref
```
Added value: +"#/$defs/SearchResult"
```

removedOutput schema / properties / results / items / properties

Removed value: -{
-  "score": {
-    "anyOf": [
-      {
-        "type": "number"
-      },
-      {
-        "type": "null"
-      }
-    ],
-    "default": null,
-    "title": "Score"
-  },
-  "snippet": {
-    "title": "Snippet",
-    "type": "string"
-  },
-  "title": {
-    "title": "Title",
-    "type": "string"
-  },
-  "url": {
-    "title": "Url",
-    "type": "string"
-  }
-}

removedOutput schema / properties / results / items / required
```
Removed value: -[
-  "title",
-  "url",
-  "snippet"
-]
```
removedOutput schema / properties / results / items / title
```
Removed value: -"SearchResult"
```
removedOutput schema / properties / results / items / type
```
Removed value: -"object"
```

First observedJul 9, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description does not need to restate that. It adds valuable behavioral context by noting that search_depth='advanced' incurs higher cost and that topic='news' or 'finance' narrows results, insights not present in the annotations. This goes beyond the structured data, though it does not mention potential rate limits or pagination, which could be useful.

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 three sentences, front-loaded with the primary purpose, followed by parameter guidance. Every sentence adds distinct value, with no filler or redundancy. It is appropriately concise while covering purpose, use cases, and parameter nuances.

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?

Given the tool's moderate complexity, full schema coverage, and read-only annotation, the description supplies all essential information: what it does, when to use it, and how to tailor parameters. The presence of an output schema means return value details are unnecessary, so the description is fully sufficient for agent selection and invocation.

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%, so the baseline is 3, but the description enriches parameter meaning by linking search_depth to complex research queries and cost, and topic to specific content domains (news, finance). These usage-oriented hints help the agent make better parameter choices than the bare schema descriptions alone.

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 identifies the tool as a real-time web search via Tavily, stating its purpose for current events, fact-checking, and research. This distinguishes it from the sibling tools, which are specific data lookups or calculations, leaving no ambiguity about what this tool does.

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

Usage Guidelines4/5

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

The description provides clear use cases (current events, fact-checking, research) and practical guidance on when to adjust parameters (search_depth for complex queries, topic for news/finance). However, it does not explicitly compare with alternatives like http_fetch or delegate_to_agent, so it lacks explicit exclusionary guidance, earning a 4 rather than a 5.

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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TDQS

A3.7/5.0

Disambiguation3/5

Most tools target distinct data sources, but several near-duplicates exist: get_token_approvals/get_wallet_approvals, get_defi_positions/get_wallet_positions, and get_wallet_portfolio/get_eth_balance. The descriptions do cross-reference and clarify the differences, so an agent can disambiguate with effort, but names alone are not enough.

Naming Consistency4/5

The dominant get_<noun> pattern is clear and nearly all names use lowercase snake_case with verb-first conventions. A few tools like calculate, record_predictions, http_fetch, and web_search break the get_ pattern, but the overall style remains predictable.

Tool Count2/5

34 tools is excessive for a single server, even for a broad DeFi/onchain analytics domain. The count is inflated by generic utilities such as calculate, count_text_stats, web_search, and http_fetch, plus multiple overlapping data-retrieval endpoints, making the surface hard to scan.

Completeness4/5

The set covers an unusually wide range of domain operations: prices, balances, portfolio/positions, approvals, yields, TVL, DEX quotes/volume, transactions, blocks, gas, ENS, contract reads, and risk assessments. It is view-only by design, so missing write/transaction tools is acceptable; minor gaps like address-based token pricing or transaction simulation are workaround-able.

Resources

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