exportGeneric fallback to any data.stortinget.no/eksport resource. Use for endpoints without a dedicated tool, e.g. resource "moter" (meetings), "komiteer" (committees) with params {sesjonid}. ?format=json is added automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| params | No | Query params, e.g. {"sesjonid": "2023-2024"}. Do not include format. | |
| resource | Yes | Endpoint name under /eksport, e.g. "moter", "komiteer", "sesjoner". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "params": {
+ "sesjonid": "2023-2024"
+ },
+ "resource": "moter"
+ },
+ {
+ "resource": "komiteer"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds a valuable behavioral detail: '?format=json is added automatically' and instructs users not to include format in params. This goes beyond annotations but is not a rich behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, front-loaded with purpose, and includes necessary examples and caveats without any waste. Every sentence contributes meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, usage scenarios, examples, and the automatic format inclusion. Since there is no output schema, it could have offered a bit more on return values, but the tool is a generic fallback and the description is adequately complete for its scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 extra value by providing examples of resource names and params (e.g., {sesjonid}), and by clarifying that format should not be included in params. This enhances understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a generic fallback to any data.stortinget.no/eksport resource, with concrete examples (moter, komiteer). It distinguishes itself from sibling tools by explicitly stating it is for endpoints without a dedicated tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: 'Use for endpoints without a dedicated tool.' This implies that if a dedicated sibling tool exists, it should not be used. It does not explicitly name alternative tools, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools are near-duplicates: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all route questions to the same underlying toolset with only minor differences. Additionally, the five polymarket_* tools overlap significantly in purpose, and the mix of Storting parliament tools with a general-purpose data platform creates confusion about which tool is appropriate.
Tool names use snake_case but with inconsistent conventions. Some are verb-first (get_, list_, discover_, validate_), while others are noun-first (entity_profile, bet_research, recent_alerts). There are predictable prefixes like ask_pipeworx and polymarket_, but overall the naming pattern is not uniform, making it harder to predict tool names.
With 38 tools, the count exceeds the 25-tool threshold for 'too many.' Many tools are unrelated to the server name 'Storting No' (which implies a Norwegian parliament focus), and the broad range of data-research and prediction-market tools feels bloated for the apparent scope. A smaller, more focused set would improve coherence.
The Storting-related tools cover the main parliamentary entities (cases, parties, representatives, sessions, votes) and include an export fallback for any additional data.stortinget.no resource. The Pipeworx side has meta-tools (ask, discover, suggest) and specialized analyses (entity_profile, validate_claim, polymarket_*). However, there are notable gaps, such as no direct tool for searching parliamentary speeches or committee documents without relying on the generic export, and the mixed domains leave some workflows incomplete.