Parsley - Buyer Intent Signals
Server Details
Query buyer intent signals, MEDDIC qualifications, and lead scores from Parsley.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- peterjduffy/parsley-mcp
- GitHub Stars
- 0
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Tool Definition Quality
Average 3/5 across 8 of 8 tools scored. Lowest: 2.4/5.
Each tool targets a distinct aspect: analytics overview, conversation listing, detailed conversation, hot leads, knowledge gaps, enrichment, MEDDIC summary, and search. No overlapping or ambiguous tools.
All tool names follow a consistent get_verb_noun pattern in snake_case with no deviations, making the API predictable.
8 tools cover the domain of buyer intent signals without being excessive or insufficient. Each tool serves a clear purpose.
Comprehensive coverage: analytics, conversation management, lead identification, enrichment, MEDDIC analysis, knowledge gap detection, and search. No obvious missing functionality for a read-only intent signal server.
Available Tools
8 toolsget_analytics_summaryBInspect
Dashboard-level overview: views, conversations, lead counts, conversion rate.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It only lists output metrics without disclosing whether the operation is read-only, requires authentication, aggregates data, or has performance implications.
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, front-loaded sentence that conveys the tool's purpose without any extraneous 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 lists the metrics returned, providing some return context, but it does not explain how the 'days' parameter affects the output, nor does it cover error conditions or edge cases. Given no output schema, more detail would be beneficial.
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 'days' parameter is documented in the schema with type and constraints, but the description does not mention it or explain its effect on the result. With 0% schema description coverage, this is a significant gap.
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 a dashboard-level overview listing specific metrics: views, conversations, lead counts, conversion rate. This distinguishes it from sibling tools like get_conversation_detail or get_hot_leads which focus on specific areas.
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 implies usage for a high-level summary but provides no explicit guidance on when to use or avoid it, nor does it mention alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_conversation_detailAInspect
Get full details of a single conversation including MEDDIC signals, engagement metrics, and enrichment data.
| Name | Required | Description | Default |
|---|---|---|---|
| conversation_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the tool returns full details with specific data types, but does not explicitly state it is read-only, require permissions, or describe side effects. Basic transparency is present but incomplete.
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, well-structured sentence of 17 words. It is front-loaded with the verb and resource, and every word adds value. No superfluous content.
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 has one parameter and no output schema, the description adequately outlines the return components (MEDDIC signals, engagement metrics, enrichment data). It covers the essential context for a read operation, though it could optionally mention the read-only nature or typical use cases.
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 input schema has one parameter (conversation_id) with 0% schema description coverage. The description adds no explanation of the parameter's format, example, or usage beyond the obvious implication from 'single conversation'. It does not compensate for the lack of schema documentation.
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 verb 'Get', the resource 'full details of a single conversation', and specifies the included components (MEDDIC signals, engagement metrics, enrichment data). This distinguishes it from sibling tools like get_conversations (list) or get_meddic_summary (summary only).
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 implies use when full detail of a single conversation is needed, but does not explicitly state when to avoid this tool or mention alternatives. Sibling tool names are known from context, but no direct guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_conversationsBInspect
List recent chatbot conversations with filtering by lead quality, intent signal, and date range.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| limit | No | ||
| lead_quality | No | ||
| intent_signal | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states it lists conversations, with no mention of side effects, authentication needs, rate limits, or response format. The tool is likely read-only, but this is not stated.
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 front-loads the key information: action, resource, and filter capabilities. Every word earns its place with no verbosity or repetition.
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 complexity (4 parameters with 0% schema coverage, no output schema, no annotations), the description is too sparse. It does not clarify defaults, pagination (limit), sorting, or the meaning of quality/signal values. A more complete description would include at least basic parameter explanations.
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 input schema has no descriptions (0% coverage), and the tool description only broadly mentions 'filtering by lead quality, intent signal, and date range'. It does not explain what individual parameters like 'days' or 'limit' control, nor the exact meaning of enum values. The description adds minimal value beyond the schema structure.
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 verb 'List' and the resource 'chatbot conversations', and specifies filtering by lead quality, intent signal, and date range. This distinguishes it from siblings like get_conversation_detail (which would retrieve a single conversation) and get_hot_leads (which focuses only on hot leads).
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 implies the tool is for listing conversations with filters, but it does not explicitly state when to use it versus alternatives like search_by_intent or get_analytics_summary. No explicit exclusions or prerequisites are provided, which is adequate but not strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_hot_leadsCInspect
Get all hot and warm leads with MEDDIC evidence. The morning briefing tool.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| include_warm | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behavior such as data freshness, response format, or side effects. The tool is implicitly read-only but not confirmed.
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?
Two concise sentences with no extraneous text. However, the second sentence adds little value beyond branding.
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?
Lacking details on output, parameter semantics, and behavioral traits. For a tool with two parameters and no output schema, the description should provide more context for completeness.
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 description coverage is 0%, but the description does not explain the parameters 'days' or 'include_warm' beyond their names and default values. This leaves the agent without guidance on how to use them.
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?
Clearly states it retrieves hot and warm leads with MEDDIC evidence and labels it as a morning briefing tool. However, it does not explicitly differentiate from sibling tools like get_analytics_summary or get_meddic_summary.
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?
No explicit guidance on when to use this tool versus alternatives. The phrase 'morning briefing tool' implies a daily use case, but there is no when-not or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_knowledge_gapsCInspect
Surface unanswered questions from chatbot conversations, grouped by topic.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| limit | No | ||
| topic | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the action (surfacing unanswered questions) but omits critical traits: it does not confirm read-only behavior, mention authentication requirements, rate limits, or any side effects.
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, front-loaded sentence that conveys the core purpose without any wasted words. Every word earns its place.
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 3 parameters with no descriptions, no output schema, and no annotations, the description is severely incomplete. It does not explain what 'unanswered' means, how 'grouped by topic' is implemented, what the response format looks like, or how to interpret results.
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 description coverage is 0%, and the description adds no meaning to the parameters (days, limit, topic). The description does not hint at how these parameters influence results or provide format or constraints beyond what the schema already defines.
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's purpose: to surface unanswered questions from chatbot conversations, grouped by topic. The verb 'Surface' is specific, and the resource 'unanswered questions from chatbot conversations' is distinct from sibling tools like get_conversations or get_analytics_summary.
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 provides no guidance on when to use this tool versus alternatives (e.g., get_conversations for full conversations, search_by_intent for intent-based queries). No explicit context or exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_lead_enrichmentBInspect
Get extracted company, role, timeline, and budget context from conversations.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| has_company | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides some transparency by listing extracted data types, but it does not disclose error handling, data limits, or whether the tool modifies data. The 'extracted' term suggests read-only, but this is not explicit.
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 focused sentence, front-loaded with the key output. It is concise but omits parameter context, which is acceptable for a short desc if schema covers, but here it doesn't.
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 two parameters, no output schema, and no annotations, the description should explain how parameters affect output. It does not, leaving the agent to guess the function's behavior beyond the basic output type.
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 0%, and the description adds no meaning to parameters 'days' and 'has_company'. The agent cannot infer what these parameters control (e.g., time range, company filter) from the description alone.
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?
Description clearly states the tool 'gets extracted company, role, timeline, and budget context from conversations.' This specific verb and resource list distinguishes it from siblings like get_conversations or get_analytics_summary, which serve different purposes.
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 implies usage for enrichment data but does not explicitly state when to use this over siblings (e.g., get_conversations, get_conversation_detail) or provide exclusions. Usage context is implied but not clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_meddic_summaryCInspect
Aggregate MEDDIC signal distribution across all conversations.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It only states 'across all conversations' suggesting scope, but omits details like data freshness, handling of empty results, or error states.
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 concise (one sentence) and front-loaded, but the extreme brevity sacrifices necessary details. It is not verbose, but borderline underspecified.
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 (one optional parameter, no output schema), the description is minimally acceptable, but it fails to explain the return format or how 'MEDDIC signal distribution' is structured, leaving gaps for an agent.
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 description does not mention the single parameter 'days' at all. With 0% schema description coverage, the agent gets no semantic meaning from the description about what 'days' controls (e.g., time range).
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 aggregates MEDDIC signal distribution across conversations, specifying a distinct verb 'aggregate' and resource 'MEDDIC signal distribution'. It is easily distinguishable from siblings like 'get_analytics_summary' which likely handles broader analytics.
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?
No guidance is provided on when to use this tool versus alternatives like 'get_analytics_summary' or 'get_conversations'. The description lacks any when-to-use, when-not-to-use, or contextual hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_by_intentCInspect
Find conversations matching specific MEDDIC signals, intent score, or topic.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| topic | No | ||
| meddic_signals | No | ||
| min_intent_score | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It does not disclose any behavioral traits such as pagination, authorization, data limitations, or output format. Only high-level purpose.
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?
Extremely concise (one sentence, 12 words), but lacks necessary details. Front-loads the purpose, but the brevity sacrifices completeness. A balanced score for minimalism at the cost of clarity.
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?
For a tool with 4 parameters, no output schema, and no annotations, the description is too minimal. It does not cover default values, ranges, or the relationship between parameters sufficiently.
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 description coverage is 0%. Description does not explain any parameters, leaving the schema's enums and defaults unexplained. No added meaning 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 states the verb 'Find' and resource 'conversations' with specific filters (MEDDIC signals, intent score, topic). It differentiates from sibling tools like 'get_conversations' which likely lists all conversations, but does not explicitly distinguish itself.
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?
No guidance on when to use this tool versus alternatives like 'get_conversations' or 'get_hot_leads'. No mention of prerequisites or when not to use it.
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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