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Pega DX MCP Server

Pega DX MCP Server

by marco-looy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

get_list_data_view

Retrieve list data views using advanced querying with pagination, filtering, sorting, aggregation, and distinct values.

Instructions

Retrieve list type data view with advanced querying capabilities. Supports 4 distinct use cases:

  1. Standard Data Retrieval: Get data with pagination, filtering, and sorting Example: { "dataViewID": "D_Employees", "query": { "select": [{"field": "Name"}, {"field": "Age"}], "filter": { "filterConditions": { "F1": { "lhs": {"field": "Department"}, "comparator": "EQ", "rhs": {"value": "IT"} } }, "logic": "F1" } }, "paging": { "pageSize": 100 } }

  2. Aggregated Data: Get aggregated data with optional grouping Example: { "dataViewID": "D_Employees", "query": { "aggregations": { "AvgAge": { "field": "age", "summaryFunction": "AVG" } }, "select": [{"field": "Department"}] }, "paging": { "maxResultsToFetch": 2000 } }

  3. Distinct Values: Get unique values from filtered lists Example: { "dataViewID": "D_Employees", "query": { "select": [{"field": "Department"}], "distinctResultsOnly": true }, "paging": { "maxResultsToFetch": 1000 } }

  4. Non-queryable Data Views: Simple data retrieval without querying Example: { "dataViewID": "D_SimpleData", "dataViewParameters": { "param1": "value1", "param2": "value2" } }

Filter comparators supported: boolean (IS_TRUE, IS_FALSE, IS_NULL, IS_NOT_NULL, EQ, NEQ), string (EQ, NEQ, IN, NOT_IN, IS_NULL, IS_NOT_NULL, STARTS_WITH, NOT_STARTS_WITH, ENDS_WITH, NOT_ENDS_WITH, CONTAINS, NOT_CONTAINS), number/date (EQ, NEQ, IN, NOT_IN, GT, GTE, LT, LTE, ISNULL, ISNOTNULL).

Aggregation functions: COUNT, MAX, MIN, DISTINCT_COUNT. For numbers: SUM, AVG.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional query object for filtering, sorting, aggregation, and field selection. If not specified, retrieves data as a regular data view.
pagingNoOptional pagination configuration. Can specify either maxResultsToFetch or pageNumber/pageSize combination, but not both.
dataViewIDYesData view ID. Example: "D_CaseList"
dataViewParametersNoParameters for parameterized data views. Key-value pairs. Example: {"CustomerID": "C-123"}
sessionCredentialsNoOptional session-specific credentials. If not provided, uses environment variables. Supports two authentication modes: (1) OAuth mode - provide baseUrl, clientId, and clientSecret, or (2) Token mode - provide baseUrl and accessToken.
useExtendedTimeoutNoOptional flag that works only if the data view is sourced by a report definition. When set to true, increases timeout to 45 seconds. Otherwise, timeout is 10 seconds.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.0.0
    • changedInput schema / properties / dataViewID / description
      Previous value: -"ID of the data view to retrieve data from. Must be a valid data view identifier that exists in the Pega system. Example: \"D_Employees\", \"D_CustomerList\""New value: +"Data view ID. Example: \"D_CaseList\""
    • changedInput schema / properties / dataViewParameters / description
      Previous value: -"Optional parameters for the data view if it has mandatory parameters. Key-value pairs where keys are parameter names and values are parameter values. Example: {\"param1\": \"value1\", \"param2\": \"value2\"}"New value: +"Parameters for parameterized data views. Key-value pairs. Example: {\"CustomerID\": \"C-123\"}"
    • addedInput schema / properties / sessionCredentials
      Added value: +{
+  "description": "Optional session-specific credentials. If not provided, uses environment variables. Supports two authentication modes: (1) OAuth mode - provide baseUrl, clientId, and clientSecret, or (2) Token mode - provide baseUrl and accessToken.",
+  "properties": {
+    "accessToken": {
+      "description": "Direct access token (required for token mode)",
+      "type": "string"
+    },
+    "apiVersion": {
+      "default": "v2",
+      "description": "API version (optional, defaults to v2)",
+      "type": "string"
+    },
+    "baseUrl": {
+      "description": "Pega base URL (required if providing credentials)",
+      "type": "string"
+    },
+    "clientId": {
+      "description": "OAuth2 client ID (required for OAuth mode)",
+      "type": "string"
+    },
+    "clientSecret": {
+      "description": "OAuth2 client secret (required for OAuth mode)",
+      "type": "string"
+    },
+    "sessionId": {
+      "description": "Optional session ID. If not provided, a new session will be created.",
+      "type": "string"
+    },
+    "tokenExpiry": {
+      "description": "Token expiry in seconds from now (optional for token mode)",
+      "type": "number"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses key behavioral traits: supported use cases, filter comparators, aggregation functions, paging limitations, extended timeout conditions, and authentication modes. It also notes constraints like distinctResultsOnly cannot be used with aggregation.

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?

The description is well-structured with numbered use cases, tables for comparators, and clear examples. It is somewhat lengthy but every section adds value. It front-loads the purpose and provides progressive detail.

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

Completeness4/5

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

Given the complexity (6 parameters, nested objects, no output schema), the description is comprehensive. It covers all use cases, explains each parameter, and provides examples. However, it does not explicitly describe the return format or structure of the response, which would be helpful.

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 coverage is 100%, so baseline is 3. The description adds significant value by providing extensive examples, enumerating supported comparators and aggregation functions, and explaining parameter interactions (e.g., paging modes, authentication options). This goes beyond the schema descriptions.

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's purpose: 'Retrieve list type data view with advanced querying capabilities.' It then enumerates four distinct use cases with concrete examples, making it easy for an agent to understand exactly what the tool does and how it differs from siblings like get_data_view_count or get_data_view_metadata.

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

Usage Guidelines3/5

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

While the description provides detailed examples and use cases, it does not explicitly guide when to use this tool versus alternatives like get_data_view_count for counts or other data retrieval tools. Usage is implied but not contrasted with siblings.

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

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