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Glama
ibkortex

kortex-mcp

Official
by ibkortex
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
KORTEX_API_KEYYesAPI key in `kx_live_<id>_<secret>` format
KORTEX_API_URLNoBase URL of the Kortex backendhttp://localhost:8000

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_collectionsA

List all collections accessible to this API key.

Returns a list of collections, each containing:

  • id: unique collection identifier (use this in retrieve)

  • nombre / descripcion: human-readable name and description — read these to understand what a collection contains before deciding whether to query it

  • availableVersions: logical version labels you can query (e.g. ["v1", "v2"])

Call this before retrieve to know which collection IDs and version labels are available.

retrieveA

Semantic search across accessible collections using Amazon Bedrock Knowledge Bases.

Args: query: Natural-language question or search phrase. collections: Which collections (and optionally which version) to search. Each entry is either: - "collection_id" → search that collection at its default version - "collection_id:label" → search that collection at the given version label Omit (or pass null) to search across all collections accessible to the API key, each at its default version. Use list_collections to discover IDs and labels. number_of_results: Maximum number of passages to return (default 10).

Returns a list of results, each with:

  • collectionId / versionLabel: which collection and version the passage came from

  • content: the retrieved text passage

  • score: relevance score (higher is more relevant)

  • sourceUri: original document URI when available

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.5/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: list_collections is for discovery of available collections, while retrieve performs semantic search. There is no overlap or ambiguity between them.

Naming Consistency4/5

list_collections follows a verb_noun pattern, but retrieve is a single verb without an explicit object. Both are imperative and readable, though not perfectly uniform.

Tool Count3/5

With only two tools, the server feels minimal but just barely adequate for its narrow scope of collection discovery and search. It sits on the lower boundary of acceptable tool count.

Completeness4/5

The server covers the essential workflow: listing collections to discover IDs and versions, then retrieving search results. There are no obvious dead ends, though a more detailed collection metadata endpoint could be considered a minor gap.

Maintenance

ActivitySlowing
ResponsivenessNo issues

Resources