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scientific-papers-mcp

by tofunori

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Find relevant research papers by combining semantic and keyword matching, with optional filters and ranked results from your Zotero library.

Instructions

Perform hybrid semantic + keyword search across research papers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alphaNoBalance between semantic (1.0) and keyword (0.0) search (default: 0.5 for balanced search)
queryYesSearch query (e.g., "glacier albedo feedback mechanisms")
top_kNoNumber of results to return (default: 10)
sourceNoSearch source - 'local' (fast), 'cloud' (remote), or 'default' (use config)default
use_rrfNoUse Reciprocal Rank Fusion (True) or alpha weighting (False)
text_filterNoOptional full text filter (JSON string) Examples: - Regex: '{"$regex": "MODIS.*MOD10A1"}' - Contains: '{"$contains": "albedo"}' - AND: '{"$and": [{"$contains": "Alaska"}, {"$contains": "glacier"}]}' - OR: '{"$or": [{"$contains": "MODIS"}, {"$contains": "Sentinel"}]}'
rrf_k_parameterNoRRF smoothing parameter k (higher = more uniform ranking)
rrf_dense_weightNoWeight for dense semantic results in RRF (0.7 = 70%)
rrf_sparse_weightNoWeight for sparse keyword results in RRF (0.3 = 30%)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it does almost none of it. A one-line statement omits cost/latency differences between sources, ranking behavior (RRF vs alpha weighting), and any limit or failure behavior; it relies entirely on the schema to convey mechanics, which is not the description's job.

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?

A single well-formed sentence with the core operation front-loaded and no filler. It is efficient, though the extreme brevity leaves the tool under-explained relative to its nine parameters.

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

Completeness3/5

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

The rich schema (100% coverage) and an output schema cover the mechanical details, so the description does not need to explain return values. What it still lacks is the contextual framing an agent needs: how this hybrid search relates to its four search_* siblings and which one to prefer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and every parameter — alpha, top_k, source, use_rrf, rrf_k_parameter, and the RRF weights — is documented in the schema with defaults and examples. The description adds no parameter meaning beyond that, so the baseline of 3 is appropriate.

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?

States a specific verb and resource ('hybrid semantic + keyword search across research papers') that an agent can act on immediately. However, it gives no signal to distinguish it from siblings like search_fulltext, search_by_author, or search_by_year, which all search the same corpus by different means.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus the sibling search tools. An agent must infer that 'hybrid' is the general-purpose option and that search_fulltext is the keyword-only path, which is never stated. No exclusions, prerequisites, or fallback conditions are given.

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