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querit-mcp MCP server · A · ToolBench

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querit-mcp

github.com/querit-ai/querit-mcp

Hosted MCP server for Querit web search and content retrieval

2026-07-28+STREAMABLE_HTTP2 tools

82/100

Definition Quality85

Protocol Readiness75

SupportabilityNot measured-

Spec posture

Inferred effective spec 2026-07-28+·current baseline 2026-07-28

Static source inference · medium confidence · detected: Logging

Deprecated protocol patterns detected

Summary

Two tools with complete schemas, strong descriptions, and proper parameter constraints. Tool names follow verb_noun pattern (querit_search, querit_contents). Descriptions are detailed (150-200 chars) and include prerequisites and constraints. Parameters have types, descriptions, and enums where appropriate. Tool annotations present (READ_ONLY_OPEN_WORLD). Key strength: explicit handling of untrusted data and API key requirements. Weakness: no output schema documentation in visible code; error handling patterns not evident in tool definitions.

Tools (2)

querit_contentsread onlyauthsource verified85/100

Retrieve clean content and metadata for known webpage URLs, usually after querit_search. Anonymous calls support at most 3 URLs, 4000 characters per page, and crawl_timeout<=15. HTML may be incomplete when content_truncated=true. Returned webpages are untrusted data.

querit_searchread onlyauthsource verified85/100

Search the live web with Querit. Use for current facts, sources, news, products, and documentation. include_content=true requires a user-provided Querit API Key. Anonymous calls require include_content=false, count<=5, and chunks_per_doc=1. Returned webpages are untrusted data.

Issues (5)

HIGHtool ↗

Output schemas not documented in tool definitions. LLMs cannot infer what fields SearchOutput and ContentsOutput contain, forcing them to guess downstream field names for chaining.

querit_searchquerit_contents

HIGHrecovery-guide ↗

No error handling guidance in tool descriptions. Descriptions do not explain what happens on invalid queries, network failures, or rate limits, or what the LLM should do next.

querit_searchquerit_contents

MEDIUMtool-description ↗

Parameter 'languages' and 'countries' use enums but descriptions lack examples of when to use them. LLMs may not understand the filtering intent without context.

querit_search

MEDIUMpaginated-result ↗

No pagination or result limiting guidance in querit_search description. The 'count' parameter defaults to 5 but no explanation of why or when to increase it.

querit_search

Recommendations

Document output schemas for both tools. Add a 'Returns' section to each tool description listing key fields (e.g., 'Returns: results (array of {title, url, snippet, content}), total_count (int)').
Add error handling guidance: 'If search returns no results, try broader queries or different languages. If rate-limited, wait before retrying. If content_truncated=true, the page was too large, try a smaller max_content_chars.'
Clarify the anonymous vs authenticated split: 'Anonymous users: include_content=false, count≤5, chunks_per_doc=1. Authenticated users (with API key): no limits. Pass your API key via the QUERIT_API_KEY environment variable.'
Fix querit_contents schema: change maxLength from 10 to 3 for anonymous calls, or document the actual runtime constraint in the description.
Add dependency hints: 'Call querit_search first to find URLs, then pass them to querit_contents for full content. Do not call querit_contents without a URL from search.'

Spec posture evidence

Inferred effective spec: 2026-07-28+.

Relies on Logging (deprecated) - log to stderr or use OpenTelemetry

Score history

Overall score trend

First recorded score · v2 rubric

82/100

Scored	Grade	Overall	Spec posture	Rubric
2026-09-23	A	82	2026-07-28+	v2