Skip to main content
Glama

Maven Central

by io.github.pipeworx-io

Search Within a Source

search_within
Read-onlyIdempotent

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text to search inside (max ~200K chars).
limitNoMax passages to return (1-20, default 5).
queryYesNatural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds significant behavioral details: underlying model (BGE-base-en), chunking (500-char overlapping windows), limit (200K chars truncated and flagged), and return fields (character offsets, similarity scores). No contradiction with annotations.

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 concise: two sentences plus a technical note. It is front-loaded with purpose and usage, and every sentence earns its place without redundancy.

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?

Despite no output schema, the description explains return format (passages with offsets and similarity scores) and behavior for oversized inputs (truncation flagged). This is complete for a search tool.

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 description coverage is 100% with each parameter described. The description adds examples for 'query', clarifies the cap for 'text', and mentions default for 'limit'. This adds value beyond the schema, though schema is already good.

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 states the tool does semantic search inside a fetched record. It uses specific verbs and resources, and distinguishes from siblings like 'search' and 'ask_pipeworx_grounded' by emphasizing internal search over a provided text.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'Use when the record is too big to cram into the prompt.' Also provides an alternative workflow: 'Pairs with ask_pipeworx_grounded.' This helps the agent choose wisely.

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

All Maven Central toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes, especially ask_pipeworx, ask_pipeworx_beta (explicitly identical right now), ask_pipeworx_grounded, and deep_research. The Polymarket tools are more distinct, but the boundary between Maven search tools and broader discovery tools like search, search_by_coords, discover_tools, and suggest_questions is not always obvious.

Naming Consistency2/5

Naming is a mix of snake_case actions, branded prefixes like ask_pipeworx_*, polymarket_*, and pipeworx_*, plus inconsistent patterns like ai_visibility_check vs scan_competitor_ai_presence. Some clusters are internally consistent, but the overall set follows no predictable convention.

Tool Count2/5

35 tools is heavy for a server named 'Maven Central', and only a handful actually relate to Maven artifacts. The rest are Pipeworx research, prediction-market, memory, subscription, and utility tools, making the set feel sprawling rather than purpose-scoped.

Completeness3/5

For the Maven Central domain, search, coordinate lookup, version listing, and latest-version retrieval cover core read-only needs. However, there is no direct artifact metadata/POM/dependency inspection, and the unrelated Pipeworx and Polymarket tools dilute the surface without filling obvious gaps in the stated domain.

Resources