Stratalize Oracle
Server Details
Crypto price and threshold consensus with ML-DSA-65 attestation and Base anchoring.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4/5 across 3 of 3 tools scored.
Each tool has a distinct purpose: one provides an overview/catalog, one verifies current price, and one resolves a price threshold. No overlap in functionality.
All tools follow a consistent 'get_verb_noun' pattern (get_resolve_price_threshold, get_stratalize_overview, get_verify_crypto_price), ensuring predictability.
With only 3 tools, the count is slightly low, but the overview tool acts as a discovery mechanism, making the set feel cohesive for a gateway server.
The server claims to cover multiple domains (finance, healthcare, etc.) but only provides crypto-related tools. Core operations like listing assets or historical data are missing, leaving significant gaps.
Available Tools
3 toolsget_resolve_price_thresholdARead-onlyInspect
Resolve whether a crypto asset is above or below a threshold via multi-source consensus for settlement and verification workflows.
| Name | Required | Description | Default |
|---|---|---|---|
| fiat | No | usd | |
| symbol | Yes | ||
| direction | Yes | ||
| threshold | Yes | ||
| tolerance_pct | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context by revealing the 'multi-source consensus' mechanism, which informs the agent about reliability and potential latency. However, it does not describe pagination, error behavior, or rate limits.
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 and mechanism. No filler or redundancy.
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 tool has 5 parameters, no output schema, and no parameter descriptions. The description provides a high-level purpose but omits return value format, how threshold comparison is performed, the role of tolerance_pct, and any edge cases. This is incomplete for an agent to invoke the tool correctly without additional schemas.
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 does not explain individual parameters like fiat, tolerance_pct, or the exact semantics of threshold comparison. It only hints at 'above or below' and 'crypto asset', leaving the agent to infer parameter meanings. This is insufficient for a 5-parameter tool with no schema descriptions.
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: resolving whether a crypto asset is above or below a threshold. It distinguishes from siblings by emphasizing 'multi-source consensus' and the specific 'threshold' focus, which contrasts with the more general price verification implied by the sibling name get_verify_crypto_price.
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 clear context for use ('settlement and verification workflows') but does not explicitly mention alternatives or when not to use this tool. It implies a specific use case but stops short of naming sibling tools or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_stratalize_overviewARead-onlyInspect
START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description is consistent. It adds valuable behavioral context by disclosing authentication requirements and the pricing structure for different service tiers, which goes beyond the annotation fields and helps set expectations for the agent.
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 front-loaded with 'START HERE' and the core purpose, followed by compact pricing and auth details. While it packs many specifics into three sentences, each piece (pricing tiers, OAuth requirement, domain coverage) serves a functional purpose for the agent deciding whether and how to invoke the tool.
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 no parameters, no output schema, and siblings are narrow query tools, the description is complete enough. It covers what the tool returns, the domains it spans, access methods, and cost implications. It could mention the response format, but the catalog nature is clear enough for an agent to proceed.
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 zero parameters, so the baseline of 4 applies. The description correctly avoids parameter details since none exist. It adds value by explaining the tool's role and output scope, which is sufficient given no params to document.
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 opens with 'START HERE' and clearly states the tool 'Returns the complete Stratalize tool catalog', a specific verb+resource. This distinguishes it from sibling tools like get_resolve_price_threshold and get_verify_crypto_price, which focus on specific price verification rather than a broad catalog discovery function.
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 explicitly says 'Call this first to discover tools by role or vertical', providing clear when-to-use guidance. It also outlines access modes (public MCP, x402 micropayments, OAuth) giving practical context, though it does not explicitly mention when not to use the tool or alternative entry points.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_verify_crypto_priceARead-onlyInspect
Verify current crypto asset price via multi-source consensus. Returns attested consensus price with agreement score across independent sources (CoinGecko, Coinbase, Kraken).
| Name | Required | Description | Default |
|---|---|---|---|
| fiat | No | usd | |
| symbol | Yes | ||
| tolerance_pct | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare a safe read-only operation. The description adds meaningful behavioral context by disclosing that it aggregates data from independent sources (CoinGecko, Coinbase, Kraken) and returns an attested consensus price with an agreement score. However, it does not describe what happens if sources disagree or other edge-case behaviors.
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 primary purpose and immediately followed by the return value. Every word earns its place with no redundancy or fluff.
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 3 parameters and no output schema, the description provides the core purpose and return type, but omits details about parameter meanings and consensus failure behavior. It is adequate for a simple read operation but has clear gaps.
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 does not explain the meanings of symbol, fiat, or tolerance_pct. It only loosely implies that 'crypto asset price' relates to these parameters, leaving the tolerance_pct semantics particularly unclear. The description fails to compensate for the lack of schema descriptions.
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 a specific verb and resource: 'Verify current crypto asset price' with a distinctive method (multi-source consensus). It distinguishes itself from sibling tools like get_resolve_price_threshold and get_stratalize_overview by emphasizing verification and consensus rather than threshold resolution or overview.
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 when to use the tool (when you need to verify a current price via consensus) but does not explicitly mention alternatives or exclusions. No reference is made to sibling tools or when not to use this tool, so usage guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Servers
- Alicense-qualityBmaintenancePost-quantum document anchoring for AI agents. Anchor any SHA-256 hash to Algorand mainnet with ML-DSA-65 (NIST FIPS-204) signatures and receive a self-contained proof bundle verifiable offline — decades from now, without trusting any vendor.Last updated11MIT
- Alicense-qualityCmaintenanceCryptographically signed market state verification for autonomous financial agents. Ed25519 receipts, fail-closed safety, 28 global exchanges (equities, derivatives, 24/7 crypto). MCP-native, x402-payable, SMA Protocol conformant.Last updatedMIT
- AlicenseAqualityAmaintenanceMCP server for on-chain attestation and wallet trust profiles across 31 EVM chains and Solana. Privacy-preserving boolean verification, ECDSA-signed responses, compliance templates.Last updated275301MIT
- Flicense-qualityCmaintenanceCryptographically anchored, tamper-evident evidence receipts for AI agents — verified run receipts, existence-at-time proofs, and cited answers from an anchored public record. Remote MCP with proof-gated settlement; attests existence and integrity, never truth.Last updated