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Orchestra MCP Server

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Python
Remote

List assets

list_assets
Read-only

Retrieve a paginated list of assets for the credential's workspace, filtering by type, integration, account, database, schema, status, or asset ID and sorting results as needed.

Instructions

Retrieve a paginated list of assets for the workspace the credential resolves to.

Assets can be filtered by type, integration, integration account, workspace, database, schema, status, or asset ID. By default, results are sorted by created_in_integration in descending order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number. Must be greater than or equal to 1.
statusNoFilter by status. Comma-separated values are supported where the parameter accepts multiple values.
asset_idsNoFilter by asset IDs. Provide comma-separated UUIDs for multiple values.
page_sizeNoNumber of items per page. Defaults to 50; maximum 100.
asset_typeNoFilter by asset type. Comma-separated values are supported.
integrationNoIntegration identifier.
schema_nameNoFilter by schema name.
sort_columnNoColumn used to sort assets.created_in_integration
workspace_idNoFilter by integration workspace ID.
database_nameNoFilter by database name.
sort_directionNoSort direction.desc
X-Orchestra-Account-IdNoAct on this account rather than the one the credential resolves to. Omit it to use the credential's own account. An API key is issued to a single account, so it may only name that account; an OAuth token may name any account its grant covers.
integration_account_idNoFilter by the account identifier in the integration.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.1
    • changedInput schema / properties / integration / anyOf
      Previous value: -[
-  {
-    "enum": [
-      "AIRBYTE_CLOUD",
-      "AIRBYTE_SERVER",
-      "AIRFLOW",
-      "ARCH",
-      "ALTERYX_SERVER",
-      "ANTHROPIC",
-      "AWS_EC2",
-      "AWS_ECS",
-      "AWS_EMR",
-      "AWS_EKS",
-      "AWS_FIREHOSE",
-      "AWS_GLUE",
-      "AWS_LAMBDA",
-      "AWS_RDS",
-      "AWS_REDSHIFT",
-      "AWS_S3",
-      "AWS_BEDROCK",
-      "AWS_SAGEMAKER",
-      "AWS_SECRETS_MANAGER",
-      "AWS_SES",
-      "AWS_STEP_FUNCTIONS",
-      "AZURE",
-      "AZURE_CONTAINER_APPS",
-      "AZURE_DATA_FACTORY",
-      "AZURE_DATA_LAKE_STORAGE",
-      "AZURE_KEY_VAULT",
-      "AZURE_KUBERNETES_SERVICE",
-      "AZURE_LOGIC_APPS",
-      "AZURE_SYNAPSE_ANALYTICS",
-      "AZURE_VM",
-      "BAUPLAN",
-      "BOOMI",
-      "CDATA",
-      "CENSUS",
-      "CLICKHOUSE",
-      "COALESCE",
-      "COUNT",
-      "DATADOG",
-      "DATABRICKS",
-      "DATAPROC",
-      "DATAZEN",
-      "DBT",
-      "DBT_CORE",
-      "DLT",
-      "DOMO",
-      "DREMIO",
-      "DUCKDB",
-      "EMAIL",
-      "ESTUARY",
-      "ETLEAP",
-      "FABRIC",
-      "FABRIC_SYNAPSE",
-      "FIVETRAN",
-      "FORTRA",
-      "GCP_BIG_QUERY",
-      "GCP_CLOUD_RUN",
-      "GCP_CLOUD_FUNCTIONS",
-      "GCP_CLOUD_STORAGE",
-      "GCP_DATAFLOW",
-      "GCP_DATAFORM",
-      "GCP_DATASTREAM",
-      "GCP_LOOKER",
-      "GKE",
-      "GITHUB_ACTIONS",
-      "GOOGLE_CLOUD",
-      "HEVO",
-      "HEX",
-      "HIGHTOUCH",
-      "HTTP",
-      "HUBSPOT",
-      "INFORMATICA_IICS",
-      "INFORMATICA_POWERCENTER",
-      "KAFKA",
-      "KEBOOLA",
-      "KLEENE",
-      "LIGHTDASH",
-      "LINUX_SSH",
-      "MATILLION",
-      "MATILLION_ETL",
-      "METAPLANE",
-      "MICROSOFT_TEAMS",
-      "MICROSTRATEGY",
-      "MONGODB",
-      "MOTHERDUCK",
-      "MYSQL",
-      "N8N",
-      "NIMBLE",
-      "NOTION",
-      "OMNI",
-      "OPEN_AI",
-      "ORCHESTRA",
-      "PARADIME",
-      "PAGER_DUTY",
-      "PINECONE",
-      "PORTABLE",
-      "POSTGRES",
-      "POWER_AUTOMATE",
-      "POWER_BI",
-      "PREFECT_CLOUD",
-      "PYTHON",
-      "QLIK",
-      "QLIK_REPLICATE",
-      "QUICKBOOKS",
-      "RENDER",
-      "RIVERY",
-      "RUDDERSTACK",
-      "SALESFORCE",
-      "SAP",
-      "SFTP",
-      "SHAREPOINT",
-      "SIGMA",
-      "SISENSE",
-      "SLACK",
-      "SNOWFLAKE",
-      "SNOWPLOW",
-      "SODA",
-      "SQL_MESH",
-      "SQL_SERVER",
-      "STITCH",
-      "STREAMKAP",
-      "TABLEAU_CLOUD",
-      "TALEND_CLOUD",
-      "THOUGHTSPOT",
-      "TOBIKO_CLOUD",
-      "WEAVIATE",
-      "WEBHOOK",
-      "WELD",
-      "WINDOWS_SSH"
-    ],
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "enum": [
+      "AIRBYTE_CLOUD",
+      "AIRBYTE_SERVER",
+      "AIRFLOW",
+      "ARCH",
+      "ALTERYX_SERVER",
+      "ANTHROPIC",
+      "AWS_EC2",
+      "AWS_ECS",
+      "AWS_EMR",
+      "AWS_EKS",
+      "AWS_FIREHOSE",
+      "AWS_GLUE",
+      "AWS_LAMBDA",
+      "AWS_RDS",
+      "AWS_REDSHIFT",
+      "AWS_S3",
+      "AWS_BEDROCK",
+      "AWS_SAGEMAKER",
+      "AWS_SECRETS_MANAGER",
+      "AWS_SES",
+      "AWS_STEP_FUNCTIONS",
+      "AZURE",
+      "AZURE_CONTAINER_APPS",
+      "AZURE_DATA_FACTORY",
+      "AZURE_DATA_LAKE_STORAGE",
+      "AZURE_KEY_VAULT",
+      "AZURE_KUBERNETES_SERVICE",
+      "AZURE_LOGIC_APPS",
+      "AZURE_SYNAPSE_ANALYTICS",
+      "AZURE_VM",
+      "BAUPLAN",
+      "BOOMI",
+      "CDATA",
+      "CENSUS",
+      "CLICKHOUSE",
+      "COALESCE",
+      "COUNT",
+      "DATADOG",
+      "DATABRICKS",
+      "DATAPROC",
+      "DATAZEN",
+      "DBT",
+      "DBT_CORE",
+      "DLT",
+      "DOMO",
+      "DREMIO",
+      "DUCKDB",
+      "EMAIL",
+      "ESTUARY",
+      "ETLEAP",
+      "FABRIC",
+      "FABRIC_SYNAPSE",
+      "FIVETRAN",
+      "FORTRA",
+      "GCP_BIG_QUERY",
+      "GCP_CLOUD_RUN",
+      "GCP_CLOUD_FUNCTIONS",
+      "GCP_CLOUD_STORAGE",
+      "GCP_DATAFLOW",
+      "GCP_DATAFORM",
+      "GCP_DATASTREAM",
+      "GCP_LOOKER",
+      "GKE",
+      "GITHUB_ACTIONS",
+      "GOOGLE_CLOUD",
+      "HEVO",
+      "HEX",
+      "HIGHTOUCH",
+      "HTTP",
+      "HUBSPOT",
+      "INFORMATICA_IICS",
+      "INFORMATICA_POWERCENTER",
+      "KAFKA",
+      "KEBOOLA",
+      "KLEENE",
+      "LIGHTDASH",
+      "LINUX_SSH",
+      "MARIADB",
+      "MATILLION",
+      "MATILLION_ETL",
+      "METAPLANE",
+      "MICROSOFT_TEAMS",
+      "MICROSTRATEGY",
+      "MONGODB",
+      "MOTHERDUCK",
+      "MYSQL",
+      "N8N",
+      "NIMBLE",
+      "NOTION",
+      "OMNI",
+      "OPEN_AI",
+      "ORCHESTRA",
+      "PARADIME",
+      "PAGER_DUTY",
+      "PINECONE",
+      "PORTABLE",
+      "POSTGRES",
+      "POWER_AUTOMATE",
+      "POWER_BI",
+      "PREFECT_CLOUD",
+      "PYTHON",
+      "QLIK",
+      "QLIK_REPLICATE",
+      "QUICKBOOKS",
+      "RENDER",
+      "RIVERY",
+      "RUDDERSTACK",
+      "SALESFORCE",
+      "SAP",
+      "SFTP",
+      "SHAREPOINT",
+      "SIGMA",
+      "SISENSE",
+      "SLACK",
+      "SNOWFLAKE",
+      "SNOWPLOW",
+      "SODA",
+      "SQL_MESH",
+      "SQL_SERVER",
+      "STITCH",
+      "STREAMKAP",
+      "TABLEAU_CLOUD",
+      "TALEND_CLOUD",
+      "THOUGHTSPOT",
+      "TOBIKO_CLOUD",
+      "WEAVIATE",
+      "WEBHOOK",
+      "WELD",
+      "WINDOWS_SSH"
+    ],
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
  2. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true, which the description does not contradict. Beyond that it adds useful behavior: results are paginated, scoped to the credential's workspace, and default-sorted by created_in_integration descending. It does not cover pagination limits or how the account-override header behaves, keeping it out of 5 territory.

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?

Two sentences, front-loaded with what the tool returns before the filtering and sorting details. There is no filler or repetition of the title.

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?

With an output schema present, the description need not explain return values, and the rich param schema covers inputs. It gives enough context on scope, filters, and default ordering to call the tool correctly, though it omits any note on pagination boundaries or the account-override parameter's semantics.

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%, so the schema already documents all 13 parameters including defaults, enums, and comma-separated multi-value syntax. The description's filter list merely mirrors the schema at a high level and adds no format or syntax detail, so the baseline 3 applies.

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 ('Retrieve a paginated list of assets') plus the scope ('for the workspace the credential resolves to'). It is clearly a list operation distinct from get_asset_by_id, though it never names siblings explicitly, so it stops short of a 5.

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?

The description enumerates the dimensions you can filter by, which implies when to reach for this tool, but it gives no explicit when-to-use vs. when-not guidance and does not route the agent to alternatives such as get_asset_by_id for a single lookup.

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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