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Manage an external data-source connection (SFTP, AWS S3)

manage_connection
Destructive

Create, list, test, or delete a workspace connection to an external data source. Two types are supported: "sftp" and "aws_s3". For sftp, create generates a keypair and returns the public key — it must be installed in the remote server's authorized_keys before test (or a trigger using this connection) will succeed. For aws_s3, create generates an ExternalId and returns a trustPolicy plus dpfPrincipalArn — the customer must create (or update) the IAM role at roleArn with that trust policy and a permissions policy granting the S3 access DPF needs, before test will succeed. Either type must pass test before it can be used in a trigger. For a first-time "pull files from this server/bucket on a schedule" request, prefer setup_scheduled_pull, which chains create + test + create-trigger for you.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoConnection type. Required for create; defaults to "sftp".
actionYesWhich operation to perform.
roleArnNoaws_s3 only. The IAM role the customer will create/update. Required for create.
hostnameNosftp only. Remote server hostname. Required for create.
usernameNosftp only. Remote username. Optional for create; defaults to "sftpuser".
workspaceIdNoWorkspace to act on. Defaults to your only workspace if you have exactly one.
connectionIdNoExisting connection to test or delete. Required for test/delete.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo
countNoaction "list" only
accountNoaction "test", type "aws_s3" only
messageNo
roleArnNo
successNoaction "test" only
hostnameNo
usernameNo
createdAtNo
createdByNo
fileCountNoaction "test", type "sftp" only
publicKeyNo
updatedAtNo
entryCountNoaction "test", type "sftp" only
externalIdNo
connectionsNoaction "list" only
trustPolicyNo
workspaceIdNo
connectionIdNo
lastTestedAtNo
assumedRoleArnNoaction "test", type "aws_s3" only
lastTestStatusNo
dpfPrincipalArnNo

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses behavioral nuances beyond annotations: create generates a keypair and returns a public key for SFTP; for AWS S3 it returns a trustPolicy and dpfPrincipalId. It also clarifies that both types must pass test before a trigger can work. This is substantial behavioral disclosure not present in annotations (which only say destructive=true). No contradiction.

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 longer but information-dense. It packs a lot: two types, four actions, setup prerequisites, and alternative tool. The structure is logical (overview, type-specific flows, usage rule). Could be slightly tightened but the length is justified by complexity. Front-loaded with the core action list.

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?

For a complex tool with two types and multi-step setup, this description covers: the actions, per-type requirements, the test gate, and the recommended alternative tool (setup_scheduled_pull). It even explains what the create action returns (public key, trustPolicy) which is critical. An output schema exists, so return formats are elsewhere covered. Very complete.

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 covers 100% of params with descriptions, so baseline is 3. The description adds contextual meaning: roleArn is aws_s3 only, hostname/username are sftp only, connectionId needed for test/delete, workspaceId defaults to sole workspace. This clarifies which params apply to which action/type, which the schema does not. Solid upgrade over schema.

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 creates, lists, tests, or deletes workspace connections, explicitly names the two supported types (sftp, aws_s3), and distinguishes itself from the sibling tool setup_scheduled_pull by advising to prefer that tool for first-time scheduled pulls.

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?

The description explicitly explains when to use this tool versus setup_scheduled_pull, and provides per-type setup steps (install public key for SFTP, update IAM role for S3) and the test-before-use requirement. It also says what's required for each action (create requires certain fields, test/delete require connectionId).

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools map to distinct lifecycle phases and the descriptions explicitly separate overlapping-sounding concepts, such as list_data versus submit_query and the generic call_dpf_api from dedicated tools. The three finish_* tools are similarly worded but each is clearly tied to a specific preceding operation, so confusion should be limited.

Naming Consistency4/5

The tool names are uniformly snake_case and mostly follow a readable verb_noun pattern like delete_data_spec, create_workspace, and run_data_job. It is not a perfect 5 because broader names like manage_connection and manage_trigger, the generic call_dpf_api, and list_my_workspaces with its pronoun make the naming pattern less predictable.

Tool Count4/5

At 16 tools, the set is just slightly above the ideal range, but the tools generally earn their place by representing distinct steps or workflow boundaries. The start/finish pairs create some apparent redundancy, but that is a natural consequence of the multi-step file-upload flow.

Completeness4/5

The toolset provides solid coverage of the core data-platform lifecycle: workspaces, data specs, jobs, connections, triggers, scheduled pulls, status polling, and SQL querying. Some additional DPF capabilities are only reachable through the generic call_dpf_api rather than dedicated tools, and billing mutations are explicitly left outside the MCP surface, so coverage is strong but not absolute.

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