Skip to main content
Glama

Data Nl

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".

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent), description reveals embedding model (BGE-base-en), windowing (500-char overlapping), character cap (200K with truncation flag), and that passages include offsets for verification. No contradictions 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?

Three sentences: purpose, when-to-use, and technical details. No wasted words, front-loaded with key verb and resource. Highly efficient.

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?

Covers purpose, usage context, technical details (embeddings, windows, cap), pairing with sibling, and output characteristics (offsets, scores). No output schema, but description sufficiently explains return structure.

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 provides 100% coverage with parameter descriptions. The description adds real-world examples ('SEC 10-K body' for text, 'supply-chain risk' for query) and clarifies the role of each parameter in use. Could more explicitly tie 'limit' to 'top-N' but adds significant contextual value.

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 'semantic search INSIDE a fetched record,' with specific verb ('search within'), resource ('a fetched record'), and distinct use case (when record is too big for prompt). It distinguishes from siblings like ask_pipeworx_grounded.

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?

Explicit guidance: 'Use when the record is too big to cram into the prompt' and 'Pairs with ask_pipeworx_grounded: fetch... ground over relevant passages.' This clarifies when to use and when not, with an alternative sibling.

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

All Data Nl 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

A3.9/5.0
Disambiguation2/5

Several tool families have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates (the beta is currently identical), and the six polymarket_* tools plus bet_research heavily overlap in prediction-market analysis. ai_visibility_check and scan_competitor_ai_presence also serve the same core function. An agent would frequently need to read lengthy descriptions to pick the right one, and could easily misselect.

Naming Consistency3/5

Most tools follow a readable snake_case pattern, but the style is mixed: some are verb-first (ask_pipeworx, search_datasets, resolve_entity), some are domain-prefixed nouns (polymarket_edges, pipeworx_feedback), and a few are bare nouns or adjective-noun phrases (dataset, entity_profile, recent_alerts). It is not chaotic, but there is no single predictable verb_noun convention across the set.

Tool Count2/5

With 34 tools, this is above the 25+ threshold considered too many for a coherent toolset. The count is inflated by near-duplicate families (three ask_pipeworx variants, six polymarket tools) that could reasonably be consolidated. While the server covers a broad domain, the number of top-level choices creates unnecessary selection burden for agents.

Completeness4/5

For a read-focused data/research gateway, the surface is quite complete: general lookup, grounded verification, deep research, entity resolution, comparisons, change tracking, memory, subscriptions, and feedback are all present. Minor gaps exist, such as no direct fetch-by-URI tool for the pipeworx:// citations that other tools return, and the Dutch open-data tools are strictly read-only. These are workarounds rather than dead ends.

Resources