Proximens Oracle
Server Details
1000+ Generative Engine Optimization (GEO) principles exposed via MCP for AI agents.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.2/5 across 8 of 8 tools scored. Lowest: 3.6/5.
Each tool has a clearly distinct purpose: auditing URLs, comparing URLs, bulk searching, retrieving principles, statistics, categories, semantic search, and brief generation. No overlap or ambiguity.
All tools follow the consistent pattern 'proximens_oracle_verb_noun' using snake_case, e.g., audit_url, get_stats, list_categories. The naming is predictable and uniform.
8 tools is well-scoped for a knowledge base and auditing system. Each tool serves a necessary function without being excessive or sparse.
The tool set covers full lifecycle: discovery (search, list categories), retrieval (get principle), statistics, auditing (single and comparison), bulk analysis, and synthesis. No obvious gaps.
Available Tools
8 toolsproximens_oracle_audit_urlAudit URL against Proximens GEO OracleARead-onlyInspect
Pro-tier tool. Fetch a target URL, extract its content, and run a comprehensive GEO audit against all 458 Proximens Oracle principles. Returns top issues with severity (critical/major/minor), specific findings, and actionable suggestions. Use this to audit your own site, a competitor, or a client URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Target URL to audit | |
| max_issues | No | ||
| client_name | No | ||
| branche_hint | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| _wm | No | |
| url | Yes | |
| _meta | No | |
| error | No | |
| score | No | |
| status | Yes | |
| audit_id | Yes | |
| recommendations | No | |
| report_markdown | No | |
| matched_principles | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and destructiveHint=false, so the tool is safe. The description adds behavioral details: fetching, extracting, and auditing, which goes beyond annotations. No contradictions; it explains the process without mentioning side effects like network requests, which are implicit.
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 sentences focusing on action, output, and usage, with no fluff. It is efficient but could be slightly more structured (e.g., listing steps). Still well above average.
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 the main purpose and output, but it omits explanation of optional parameters and does not reference the existing output schema or annotations. Given the tool's complexity, more detail on parameters and how to interpret results would improve 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 coverage is only 25% (only 'url' described). The description does not add meaning for 'max_issues', 'client_name', or 'branche_hint', failing to compensate for the low coverage. Without parameter details, agents may misuse optional parameters.
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 fetches a URL, extracts content, and performs a GEO audit against 458 principles, returning issues with severity and suggestions. It also explicitly says to use for auditing own site, competitor, or client URL, distinguishing it from siblings like compare_urls or bulk_search.
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 advises using this tool for auditing a single URL, but does not explicitly exclude other use cases or mention when to use sibling tools like compare_urls or bulk_search. However, the context from sibling names implies differentiation, so guidelines are clear but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
proximens_oracle_bulk_searchBulk Search Proximens OracleARead-onlyIdempotentInspect
Pro-tier tool. Perform multiple natural-language searches simultaneously. Efficiently batches embeddings and parallelizes vector searches. Useful for full site-audits or keyword lists.
| Name | Required | Description | Default |
|---|---|---|---|
| queries | Yes | ||
| category | No | ||
| top_k_per_query | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| _meta | No | |
| results | Yes | |
| total_matches | Yes | |
| total_queries | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive. Description adds that it batches and parallelizes, and labels it 'pro-tier'. No contradictions.
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?
Three concise, front-loaded sentences. No fluff, each sentence adds value.
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?
Provides sufficient context for usage and behavior. Lacks parameter details, but output schema exists and sibling list clarifies niche.
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%, so description must explain parameters. Only 'queries' is implied via 'multiple natural-language searches'. 'category' and 'top_k_per_query' are not explained.
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 the tool performs multiple natural-language searches simultaneously, batches embeddings, and parallelizes vector searches. Differentiates from sibling tools like 'search_principles' and 'compare_urls'.
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?
Mentions usefulness for 'full site-audits or keyword lists', implying when to use. Lacks explicit exclusions or alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
proximens_oracle_compare_urlsCompare URLs against Proximens GEO OracleARead-onlyInspect
Pro-tier tool. Fetch two URLs (self and competitor) and run a delta-audit against Proximens Oracle principles. Returns missing principles on self and competitor, plus strategic insights.
| Name | Required | Description | Default |
|---|---|---|---|
| self_url | Yes | Your URL to audit | |
| competitor_url | Yes | Competitor URL to compare against |
Output Schema
| Name | Required | Description |
|---|---|---|
| _meta | No | |
| error | No | |
| insights | Yes | |
| self_url | Yes | |
| self_score | Yes | |
| self_matched | Yes | |
| competitor_url | Yes | |
| competitor_score | Yes | |
| delta_principles | Yes | |
| competitor_matched | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and destructiveHint. The description adds value by detailing the return type (missing principles and strategic insights). No contradictions with annotations.
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 two sentences, front-loaded with importance ('Pro-tier tool'), and every word adds value. No unnecessary 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 presence of an output schema, the description need not detail return values but does so. It covers the core functionality, though it could include high-level usage scenarios or prerequisites.
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 context by naming the parameters as 'self' and 'competitor' URLs, but doesn't add detailed semantics 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 tool's function: fetching two URLs and running a delta-audit. It uses specific verbs and resources, distinguishing it from sibling tools like the single-URL audit or bulk search.
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 hints at a premium nature ('Pro-tier tool') but does not explicitly state when to use this tool over alternatives like audit_url (for single URL) or bulk_search. More guidance on context would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
proximens_oracle_get_principleGet GEO principle by IDARead-onlyIdempotentInspect
Fetch a single GEO principle by UUID. Free tier returns summary + category + confidence only; Pro/Enterprise tiers return full text, source URL, evidence count, and validation metadata. Use this after search_principles to drill down into a specific principle.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Principle UUID (from search_principles results) |
Output Schema
| Name | Required | Description |
|---|---|---|
| id | Yes | |
| _wm | No | |
| title | Yes | |
| summary | Yes | |
| branches | No | |
| category | Yes | |
| full_text | No | |
| confidence | Yes | |
| source_url | No | |
| source_type | No | |
| upgrade_hint | No | |
| evidence_count | No | |
| source_diversity | No | |
| last_validated_at | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds significant value by explaining tier-specific data (Free vs Pro/Enterprise), which is beyond schema and annotations.
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 sentences, front-loaded with action and resource, no wasted words. Includes usage guidance and tier behavior efficiently.
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?
Despite having an output schema, the description adds tier-specific details on returned data and the usage workflow, making it fully complete for a simple fetch tool.
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 clarifies that the UUID should come from search_principles results, adding contextual 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 action ('Fetch'), the resource ('GEO principle'), and the identifier type ('UUID'), and distinguishes the tool from sibling search_principles.
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?
Explicitly advises using this tool after search_principles to drill down, providing clear context. It could mention when not to use, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
proximens_oracle_get_statsGet Oracle statisticsARead-onlyIdempotentInspect
Get aggregate statistics about the Proximens GEO Oracle: total principles, total categories, confidence distribution buckets (>=0.9, 0.8-0.9, 0.7-0.8, <0.7), and last-validated timestamp. Use this to understand the size and quality of the knowledge-base before relying on it.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| tier_hint | No | |
| fetched_at | No | |
| total_categories | Yes | |
| total_principles | Yes | |
| last_validated_at | No | |
| last_distillation_at | No | |
| confidence_distribution | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds value by specifying the exact statistics returned, thus clarifying the output beyond the annotations.
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 sentences, no fluff. First sentence enumerates the output, second sentence provides usage context. 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 no parameters and an output schema, the description fully covers the tool's purpose and when to use it. No additional information is necessary.
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?
With zero parameters, the baseline is 4. The description correctly addresses no parameters and does not need to add parameter-specific meaning.
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' and resource 'aggregate statistics', listing specific metrics (total principles, categories, confidence buckets, timestamp). It distinguishes from sibling tools like proximens_oracle_get_principle.
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 advises using the tool 'to understand the size and quality of the knowledge-base before relying on it', providing clear context. It does not explicitly exclude scenarios or name alternatives, but the advice is sufficient for a read-only summary tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
proximens_oracle_list_categoriesList GEO principle categoriesARead-onlyIdempotentInspect
List all categories used in the Proximens GEO Oracle, with the count of principles per category and a short description. Use this to discover what categories exist before filtering with search_principles. Categories include: technical, structured-data, content, ai-search, freshness, multimodal, user-signals, e-e-a-t, mobile, performance, query-intent, internal-linking, other.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| total | Yes | |
| cached | Yes | |
| categories | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable context (count per category, short description, and example categories) beyond what annotations provide, but does not disclose any additional behavioral traits like rate limits or data freshness.
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 two sentences and to the point, but the list of example categories could be streamlined or omitted if space is critical. Overall efficient and front-loaded.
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?
With no parameters and an output schema present, the description fully covers what the tool does and how to use it, including its place in a workflow.
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?
There are zero parameters and schema coverage is 100%, so no additional parameter explanation is needed. The description correctly confirms no input required.
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 lists all categories with counts and descriptions, and explicitly lists examples. It distinguishes from siblings by indicating preparatory use before search_principles.
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?
Explicitly says 'Use this to discover what categories exist before filtering with search_principles', providing clear guidance on when to use it and its relationship to a sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
proximens_oracle_search_principlesSearch GEO principles (Proximens Oracle)ARead-onlyIdempotentInspect
Semantic search over the Proximens GEO Oracle — a curated knowledge-base of 458+ Generative Engine Optimization principles distilled from research papers, vendor documentation, and patents. Free tier returns top-5 summaries; Pro tier returns top-25 with full text, source URLs, and confidence scores. Use this when you need authoritative answers about how AI search engines (ChatGPT, Perplexity, Gemini, Copilot) evaluate and cite content.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural-language search query (e.g. "schema markup for local businesses" or "how to optimize for ChatGPT citations") | |
| top_k | No | ||
| category | No | ||
| min_confidence | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| results | Yes | |
| tier_note | No | |
| query_used | Yes | |
| total_in_database | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint, so the description adds value by explaining tiered behavior (free vs pro returns) and the knowledge base composition. No contradiction with annotations.
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?
Concise, three sentences: first defines the tool, second explains tiers, third gives usage guidance. No unnecessary words, every sentence adds value.
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?
Covers core search purpose and tier differences but lacks details on parameter usage (filtering by category, confidence) and output structure beyond summaries. Given output schema exists, some return info is implied, but description could be more complete for complex queries.
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 only 25% (only query has description). The tool description does not compensate for missing parameter details (top_k, category, min_confidence). It briefly mentions top-5/top-25 but doesn't link to the top_k parameter or explain category/confidence.
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 performs semantic search over a specific knowledge base of GEO principles, with details on the size and sourcing. The verb 'search' and resource 'GEO principles' are specific, and the context suggests it's distinct from sibling tools like get_principle or bulk_search.
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?
Explicitly says 'Use this when you need authoritative answers about how AI search engines evaluate and cite content,' providing clear usage context. Does not specify when not to use or mention alternatives, but the guidance is sufficient for basic selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
proximens_oracle_synthesize_briefSynthesize Content Brief from Proximens OracleARead-onlyInspect
Generate a structured content brief (H1, H2s, FAQs, Schema) for a given topic. Uses Oracle principles to ensure the content is optimized for AI search engine visibility.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | ||
| target_branche | No | ||
| competitor_urls | No | ||
| word_count_target | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| _meta | No | |
| topic | Yes | |
| brief_id | Yes | |
| schema_markup | No | |
| faq_suggestions | No | |
| suggested_structure | Yes | |
| estimated_word_count | Yes | |
| principles_to_address | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, confirming no destructive side effects. The description adds that it generates a structured brief but provides no further behavioral details (e.g., response format, rate limits, or process). This is adequate but not enhanced beyond annotations.
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 two sentences, front-loaded with the core purpose, and contains no extraneous information. Every word contributes meaning.
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 4 parameters and an output schema exists, the description covers the main output structure but lacks detail on optional parameters and the meaning of 'Oracle principles'. It is adequate but incomplete for a tool with this complexity.
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?
With 0% schema description coverage, the description fails to explain most parameters. Only 'topic' is implied by 'given topic', but 'target_branche', 'competitor_urls', and 'word_count_target' are left undocumented. This insufficiently compensates for the schema 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 generates a structured content brief listing specific components (H1, H2s, FAQs, Schema). The mention of Oracle principles and AI search engine visibility defines its purpose precisely, and it is distinct from sibling tools like audit or search.
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 used when you need a content brief for a topic, but it does not provide explicit guidance on when to use it versus alternatives like the audit or search tools. No when-not-to-use or alternative options are mentioned.
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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