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JamBelg

MCP GraphQL Sales Server

by JamBelg
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LOG_LEVELNoLogging levelINFO
GRAPHQL_ENDPOINTNoThe GraphQL endpoint URLhttp://127.0.0.1:5001/graphql

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
graphql_queryA
Run a raw GraphQL query against the sales API.

Args:
    query: The GraphQL query string
    variables: Optional variables for the query

Returns:
    Dict containing the GraphQL response or error information
test_connectionA
Test the connection to the GraphQL endpoint.

Returns:
    Dict containing connection status
get_all_ordersA
Retrieve all orders with complete details.

Returns:
    Dict containing all orders or error information
get_order_by_idA
Retrieve a specific order by its ID.

Args:
    order_id: The order ID to search for

Returns:
    Dict containing the order details or error information
get_orders_by_customer_nameA
Retrieve all orders for a specific customer by name.

Args:
    customer_name: The customer name to search for

Returns:
    Dict containing the customer's orders or error information
get_orders_by_customer_idA
Retrieve all orders for a specific customer by ID.

Args:
    customer_id: The customer ID to search for

Returns:
    Dict containing the customer's orders or error information
get_total_spent_by_customerB
Get the total amount spent by a customer.

Args:
    customer_name: The customer name to calculate total spending for

Returns:
    Dict containing the total spent or error information
orders_after_dateA
Retrieve all orders after a given date (YYYY-MM-DD).
Note: This filters locally since the GraphQL schema doesn't have date filters.

Args:
    date: Date string in YYYY-MM-DD format

Returns:
    Dict containing filtered orders or error information
orders_between_datesA
Retrieve all orders between two dates (inclusive).

Args:
    start_date: Start date in YYYY-MM-DD format
    end_date: End date in YYYY-MM-DD format

Returns:
    Dict containing filtered orders or error information
get_order_summaryA
Get a summary of all orders including counts and totals.

Returns:
    Dict containing order summary statistics

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

A3.9/5.0

Scored across 10 tools

Disambiguation4/5

Each tool targets a distinct query pattern: order by ID, all orders, by customer name/ID, date ranges, summary, and raw GraphQL. get_orders_by_customer_name and get_orders_by_customer_id are similar but clearly differentiated by the lookup key. graphql_query could overlap with any tool but is explicitly raw and optional.

Naming Consistency4/5

Most tools follow a get_* pattern (get_order_by_id, get_all_orders, get_total_spent_by_customer), but graphql_query, test_connection, and the date-based tools (orders_after_date, orders_between_dates) deviate slightly. The naming is still intuitive and readable.

Tool Count5/5

10 tools is a well-scoped size for a sales query server. Each tool provides a distinct, useful capability without unnecessary redundancy, and the count fits comfortably within the ideal range for a focused server.

Completeness4/5

The server covers a comprehensive set of order-read operations: retrieval by ID, all, customer name/ID, date filtering, total spend, and summary statistics. A raw GraphQL query tool fills in gaps. Missing write operations and customer resource tools, but for a read-focused sales query server this is substantial.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources