installed_capacityYear-end installed generation capacity by production type (MW).
| Name | Required | Description | Default |
|---|---|---|---|
| area | Yes | Bidding-zone EIC code | |
| year | Yes | Year (e.g. 2024) |
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Query parameters sent to ENTSO-E API | |
| time_series | Yes | Array of installed capacity time series by type | |
| time_series_count | Yes | Number of time series returned |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "area": "10YDE-VE-------2",
+ "year": 2024
+ },
+ {
+ "area": "10YFR-RTE------C",
+ "year": 2023
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "query": {
+ "description": "Query parameters sent to ENTSO-E API",
+ "type": "object"
+ },
+ "time_series": {
+ "description": "Array of installed capacity time series by type",
+ "items": {
+ "properties": {
+ "business_type": {
+ "description": "Business type classification",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "in_domain": {
+ "description": "Inbound domain EIC code",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "mrid": {
+ "description": "Market Resource ID",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "out_domain": {
+ "description": "Outbound domain EIC code",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "periods": {
+ "description": "Capacity periods (typically year-end)",
+ "items": {
+ "properties": {
+ "period_end": {
+ "description": "Period end timestamp (ISO 8601)",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "period_start": {
+ "description": "Period start timestamp (ISO 8601)",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "points": {
+ "description": "Capacity data points",
+ "items": {
+ "properties": {
+ "position": {
+ "description": "Position/index in period",
+ "type": "number"
+ },
+ "value": {
+ "description": "Installed capacity in MW",
+ "type": "number"
+ }
+ },
+ "required": [
+ "position",
+ "value"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "resolution": {
+ "description": "Time resolution",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "psr_type": {
+ "description": "Production type (Solar, Wind, Nuclear, Gas, etc.)",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "time_series_count": {
+ "description": "Number of time series returned",
+ "type": "number"
+ }
+ },
+ "required": [
+ "query",
+ "time_series_count",
+ "time_series"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety traits. The description adds no further behavioral context (e.g., data freshness, aggregation level). With annotations present, the bar is lower, but the description adds minimal value beyond what annotations and schema provide.
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 a single sentence that immediately conveys the core purpose. It contains no unnecessary words and is efficiently front-loaded with the key 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?
Given the tool's simplicity (2 params, output schema exists), the description is mostly sufficient. It mentions the key output dimension 'by production type'. However, it could briefly note that results are per the specified area and year, which is implied but not explicit.
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?
The schema covers 100% of parameters with descriptions ('area' as bidding-zone EIC code, 'year' as numeric year). The description does not add any additional meaning beyond the schema, so baseline of 3 is appropriate.
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 states the tool returns 'year-end installed generation capacity by production type (MW).' It identifies the specific verb ('installed capacity') and resource ('by production type'), but does not distinguish it from the sibling tool 'actual_generation_per_type', which also involves generation capacity.
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?
There is no guidance on when to use this tool versus alternatives like 'actual_generation_per_type'. The description lacks any context about when to use this tool or when not to, and no alternatives are mentioned.
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 have overlapping or duplicate roles: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and deep_research/ask_pipeworx/discover_tools/suggest_questions all serve query routing. The five ENTSO-E tools are distinct but are lost among the unrelated Pipeworx/prediction-market tooling.
Naming mixes single verbs (remember, forget, subscribe), noun phrases (actual_load, entity_profile), verb_noun patterns (compare_entities, discover_tools), and brand-prefixed groups (pipeworx_*, polymarket_*). Snake_case is consistent, but the verb style and naming logic vary widely with no discernible overall pattern.
36 tools is too many for a server supposedly focused on ENTSO-E electricity data, especially since only 5 tools serve that domain. Even as a general data-access server, the set is heavy and includes redundant/beta variants (ask_pipeworx_beta, ask_pipeworx_grounded) that inflate the count.
The server name 'Entso E' implies electricity-market data, but only 5 of 36 tools cover generation, load, prices, capacity, and cross-border flow. Missing typical ENTSO-E operations like forecasts, balancing, or real-time grid status, while the remaining 31 tools belong to an unrelated data platform — severely incomplete for the advertised purpose.