A
licenseA
qualityC
maintenanceAI-powered spatial intelligence for landscape restoration, enabling queries on cadastral parcels, species, climate data, and policy documents across Central Asia.
16
1
Apache 2.0
narrative-engine
Server Details
Grant, investor & policy narrative generation for conservation work.
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- jdhart81/viridis-agent-fleet
- GitHub Stars
- 0
- Server Listing
- viridis-agent-fleet
Available Tools
2 toolsdescribe_agentBInspect
Fleet-standard self-description: capabilities, inputs, outputs.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
B3.4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states it describes capabilities, inputs, outputs, implying a read-only introspection. However, it fails to explicitly state it has no side effects or authentication requirements, which is minimal for a safe tool.
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?
Single, front-loaded sentence with no wasted words. Every part adds information: subject ('Fleet-standard self-description'), scope ('capabilities, inputs, outputs').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with no params and an output schema exists. Description is minimal but sufficient for a self-description tool. However, it does not hint at output format or structure, leaving some uncertainty for the agent.
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?
Tool has 0 parameters and 100% schema coverage. Per instructions, baseline is 4. Description adds no parameter info, which is acceptable since none exist.
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?
Description clearly states 'self-description: capabilities, inputs, outputs' indicating the tool describes itself. It distinguishes from sibling 'translate_narrative' by being a meta-tool. However, the phrase 'Fleet-standard' is jargon that may not be universal, slightly reducing clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus the sibling 'translate_narrative' or any alternatives. The description does not mention context or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
translate_narrativeCInspect
Translate raw ecological/agent data into a decision-maker-ready narrative.
audience_type: board_member | general_public | grant_funder |
institutional_investor | journalist | policymaker | regulator |
retail_investor | scientist
format_type: academic_paper | executive_summary | grant_proposal |
investor_deck | newsletter | policy_brief | press_release
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| request_id | No | ||
| format_type | Yes | ||
| key_message | No | ||
| payment_ref | No | ||
| agent_output | Yes | ||
| audience_type | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations (readOnlyHint, destructiveHint, etc.) are provided, so the description carries full burden. It does not disclose behavioral traits like side effects (e.g., database writes), authentication needs, rate limits, or error behaviors. The tool could be a pure transformation, but this is not explicitly stated, leaving ambiguity.
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 short (two lines plus a list) and gets to the point. However, the list is inline with newlines, which could be better structured (e.g., using bullet points). There is no unnecessary content, so it earns a high score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters, a nested object, and an output schema (not shown). The description explains the purpose and gives parameter hints for two parameters, but fails to mention that 'agent_output' is required or what it should contain. It also doesn't describe return values, though output schema exists. Given the complexity, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, so the description must compensate. It adds meaning for 'audience_type' and 'format_type' by listing possible values, but does not explain 'agent_output' (an object with no defined structure), 'key_message', 'request_id', or 'payment_ref'. The description covers only two out of six parameters, which is insufficient for a tool with many parameters.
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?
The description clearly states the tool's verb ('Translate') and resource ('raw ecological/agent data') and specifies the output ('decision-maker-ready narrative'). It also lists audience and format types, making the purpose unambiguous. However, it does not differentiate from the sibling tool 'describe_agent', so it loses some clarity.
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 provides context on when to use the tool by listing audience types and formats, implying use cases like generating a press release or policy brief. However, it does not explicitly state when not to use this tool or mention alternatives, such as when to use 'describe_agent' instead. Guidance is implicit but not thorough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
- Changed
translate_narrative2 fields changed- added
Input schema / properties / payment_refAdded value: +{ + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Payment Ref" +} - added
Input schema / properties / request_idAdded value: +{ + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Request Id" +}
2 tool updates
- First observed
describe_agent - First observed
translate_narrative
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
B3.3/5.0
Disambiguation5/5
The two tools have clearly distinct purposes: one is for self-description of the agent, the other translates ecological data into narratives for different audiences and formats. No overlap.
Naming Consistency5/5
Both tools use a consistent verb_noun pattern (describe_agent, translate_narrative), which is clear and predictable.
Tool Count3/5
With only 2 tools, the server feels thin for a 'narrative engine' domain. While not critically underpopulated, it borders on insufficient for typical multi-step workflows.
Completeness2/5
The tool surface is severely limited: only self-description and a single translation operation. Missing are tools for creating narratives from scratch, editing, comparing, or managing templates, making the set incomplete for the stated domain.