Skip to main content
Glama
klever-io

Klever MCP Server

Official
by klever-io
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
TypeScript
Hybrid

query_context

Read-onlyIdempotent

Retrieve structured knowledge entries for Klever smart contract development with filtering by type, tags, and contract type. Returns matched entries with scores and pagination.

Instructions

Search the Klever VM knowledge base for smart contract development context. Returns structured JSON with matching entries, scores, and pagination. Use this for precise filtering by type or tags; use search_documentation for human-readable "how do I..." answers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoFree-text search query. Use Klever-specific terms for best results (e.g. "storage mapper SingleValueMapper", "payable endpoint KLV", "deploy contract testnet").
typesNoFilter results by context type. Omit to search all types. Common combinations: ["code_example", "documentation"] for learning, ["error_pattern"] for debugging, ["security_tip", "best_practice"] for reviews.
tagsNoFilter by tags (e.g. ["storage", "mapper"], ["tokens", "KLV"], ["events"]). Tags are matched with OR logic — any matching tag includes the entry.
contractTypeNoFilter by contract type (e.g. "token", "nft", "defi", "dao"). Only returns entries tagged for this contract category.
limitNoMaximum number of results to return (1-100). Default: 10.
offsetNoNumber of results to skip for pagination. Use with limit to page through results. Default: 0.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the read-only/idempotent annotations, the description adds that the tool returns structured JSON with matching entries, scores, and pagination, disclosing return format and pagination behavior. 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, each earning its place: purpose, output format, and usage guidance. Front-loaded with the core action, no fluff.

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 no output schema, the description appropriately includes return format and pagination details. The 6 parameters are fully documented in the schema, and the description clarifies the tool's role relative to a key sibling, providing sufficient context.

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 coverage is 100%, so each parameter already has a detailed description. The tool description adds only a general reference to filtering by type/tags, which does not significantly enhance the schema-provided semantics, keeping the score at baseline.

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 searches the Klever VM knowledge base for smart contract development context, with a specific verb ('Search') and resource. It distinguishes from search_documentation by noting it is for precise filtering, making the purpose unambiguous.

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 this tool ('precise filtering by type or tags') and when to use the alternative ('use search_documentation for human-readable ... answers'). This provides clear when/when-not guidance and names a specific sibling tool.

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

Install Server

Other Tools