A
licenseNot graded
qualityD
maintenanceBuilds and searches knowledge graphs from input text using the cognee AI memory engine.
1
Apache 2.0
DreamThreads DreamGraph
Server Details
Parse dreams into structured context and search DreamGraph concepts without storing dream text.
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
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
2 toolsparse_dreamParse dream contextARead-onlyIdempotentInspect
Extract structured entities, actions, emotions, agency, threat, outcome, sensory cues, and recurrence from one dream narrative. This bounded tool does not generate a fixed meaning, diagnosis, or prediction, and it does not store dream text.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The user's dream narrative, supplied with their permission. | |
| recurrence | No | Optional recurrence hint supplied by the user; omit rather than infer it. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| privacy | Yes | |
| attribution | Yes | |
| structured_dream | Yes |
TDQS
A4.5/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, but the description adds valuable specifics: it 'does not store dream text' and is a 'bounded tool' that avoids interpretation. These go beyond the annotations and clarify privacy and scope, making behavior fully transparent.
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?
The description is two sentences, front-loaded with the primary action, and every phrase adds value. It is concise without sacrificing important scope and privacy details.
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?
The tool has a detailed output schema and strong annotations. The description covers behavioral scope, exclusions, and privacy, making it complete for an agent to decide when and how to use it. No critical gaps.
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 coverage is 100%, so baseline is 3. The description does not add meaning to the parameters, though it mentions 'recurrence' as an extracted entity, which could slightly confuse the role of the recurrence input parameter. No added value beyond schema, but no harm.
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 uses a specific verb 'Extract' and lists the exact resource ('structured entities, actions, emotions, agency, threat, outcome, sensory cues, and recurrence') from 'one dream narrative'. It clearly delimits scope by stating what it does not do (generate meaning, diagnosis, prediction), which distinguishes it from potential interpretive tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context that the tool is for parsing a single dream narrative and explicitly states exclusions ('does not generate a fixed meaning, diagnosis, or prediction'). It does not name the sibling tool 'search_dream_concepts' as an alternative, so it lacks explicit 'when-not-to-use' guidance relative to siblings, but the context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_dream_conceptsSearch DreamGraph conceptsARead-onlyIdempotentInspect
Search DreamGraph's stable, context-first vocabulary for a dream element or experience. Results are descriptive concepts, not universal symbolic definitions.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of matching concepts. | |
| query | Yes | A dream element or experience, such as snake, falling, ex partner, or unable to move. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| query | Yes | |
| results | Yes | |
| attribution | Yes |
TDQS
A3.8/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only and non-destructive, so the safety profile is covered. The description adds meaningful context beyond that by stating results are 'stable, context-first' and 'descriptive concepts, not universal symbolic definitions,' which helps set agent expectations about output semantics. This exceeds the minimum bar for transparency.
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?
The description is two sentences long, with the first sentence delivering the core purpose and the second clarifying the nature of results. Every word adds value, and it avoids redundancy with the title or schema.
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?
Given the existence of an output schema and comprehensive annotations, the description covers the essential context for a simple search tool. It does not elaborate on pagination or error behavior, but these are not critical for a straightforward lookup. The description satisfies the bulk of contextual needs.
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?
The input schema has 100% description coverage for both parameters, including examples and constraints. The description does not add significant parameter-level detail beyond what the schema already provides, so the baseline score of 3 is appropriate.
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 searches DreamGraph's vocabulary for a dream element or experience, using a specific verb and resource. It distinguishes itself by noting results are descriptive concepts rather than universal symbolic definitions, which hints at its unique scope. However, it does not explicitly contrast with the sibling tool parse_dream as the high-calibration example does.
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 implies usage for looking up dream-related concepts, providing a clear context for when to use it. It does not mention alternatives or exclusions, such as when parse_dream would be more appropriate. Thus, it is clear but lacks explicit when/not-to-use guidance relative to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
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TDQS
A3.9/5.0
Disambiguation5/5
parse_dream and search_dream_concepts have clearly distinct purposes: one processes a narrative into structured components, the other looks up concepts in a vocabulary. There is no overlap in what they do, so an agent can easily select the right tool.
Naming Consistency5/5
Both tool names follow a consistent verb_noun pattern: parse_dream and search_dream_concepts. The verbs are clear and the naming style is uniform, making the set predictable.
Tool Count3/5
With only two tools, the server feels thin for a domain like dream analysis. While the two tools cover basic parsing and concept lookup, the small count suggests a limited scope that may not justify a separate server.
Completeness2/5
The tools only parse narratives and search a fixed vocabulary. There is no way to store dreams, manage concepts, or generate deeper analysis/relationships, leaving significant gaps for a 'DreamGraph' service that would likely need graph operations or synthesis capabilities.