Non-custodial MCP decision layer for AI agents evaluating stablecoin allocation routes with risk scoring, security gates, evidence snapshots, execution metadata, and signed attestations.
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.
Average 2.8/5 across 4 of 4 tools scored.
Each tool has a clearly distinct purpose: market snapshot, allocation optimization, pool evidence, and protocol security. There is no overlap or ambiguity.
All tools follow the same 'get_' verb-noun pattern (get_market_snapshot, get_optimal_allocation, get_pool_evidence, get_protocol_security_status), making names predictable and easy to navigate.
With 4 tools, the server is concise and focused on core DeFi insights. While slightly on the lower side, it avoids bloat and each tool serves a meaningful function.
The tool set covers key read-only operations: market overview, allocation decisions, pool details, and security. Missing a pool listing tool, but core intelligence needs are met for a decision-support server.
get_market_snapshotCInspectReturn aggregate DaoRoute market, data coverage, and candidate pool intelligence without exposing raw datasets.
| Name | Required | Description | Default |
|---|---|---|---|
| asset | No | USDC | |
| chain | No | auto | |
| max_pools | No | ||
| verbosity | No | full | |
| risk_profile | No | conservative | |
| stablecoin_only | No | ||
| min_pool_tvl_usd | No |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavior. It states 'without exposing raw datasets' implying aggregate/safe read. But it does not mention rate limits, side effects, or authentication needs. The description is insufficient for a complete behavioral profile.
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, which is concise but lacks structure. It front-loads the purpose but omits important details. Could be more informative while still being concise.
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 7 parameters with no schema descriptions and no parameter usage in the description. While there is an output schema, the description does not help the agent parameterize the call effectively. Incomplete for this complexity level.
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%, so the description must explain parameters. It does not mention any parameter. Parameter names like 'risk_profile' and 'verbosity' need more context. The description fails to add meaning beyond parameter names and defaults.
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 aggregate market intelligence without raw datasets. It distinguishes from siblings which focus on allocation, evidence, and security. However, 'aggregate' and 'candidate pool intelligence' are somewhat vague.
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 offers no guidance on when to use this tool versus its siblings. An agent would not know if this is for quick overviews or for specific use cases. No usage context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_optimal_allocationCInspectReturn a risk-adjusted stablecoin allocation decision.
| Name | Required | Description | Default |
|---|---|---|---|
| asset | Yes | ||
| chain | Yes | ||
| max_pools | No | ||
| min_pools | No | ||
| verbosity | No | full | |
| risk_profile | Yes | ||
| time_horizon | No | flexible | |
| capital_amount | Yes | ||
| signer_address | Yes | ||
| max_slippage_bps | No | ||
| min_pool_tvl_usd | No | ||
| excluded_protocols | No | ||
| attestation_required | No | ||
| max_allocation_per_pool_bps | No |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavioral traits. It only mentions 'risk-adjusted' but omits side effects, authorization needs, rate limits, or output structure. Does not explain if the allocation is executed or merely computed.
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, which is concise, but it does not add value beyond the name. It is under-specified rather than efficiently informative.
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 complexity (14 parameters, no parameter descriptions, no output schema details shown), the description is vastly incomplete. It fails to provide necessary context for correct usage.
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 any parameter's meaning or usage. For a tool with 14 parameters, this is critically insufficient.
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 it returns a 'risk-adjusted stablecoin allocation decision', using a specific verb and resource. It distinguishes from sibling tools that provide market snapshots, pool evidence, or protocol security status.
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. Lacks context such as prerequisites, typical use cases, 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.
get_pool_evidenceBInspectReturn detailed evidence for a pool lookup: APR history, TVL, risk context, and suggested follow-up actions.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | ||
| pool_id | No | ||
| protocol | No | ||
| verbosity | No | full | |
| history_days | No | ||
| token_symbol | No |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as read-only status, rate limits, authentication requirements, or side effects. It only states what the tool returns, leaving the agent without crucial operational context.
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 concise sentence that effectively communicates the tool's purpose without extraneous words. It is front-loaded and structured well.
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 6 parameters (0 required), an output schema, and no parameter descriptions, the description is incomplete. It does not explain how input variations affect results or provide context for complex usage (e.g., filtering by chain or protocol).
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%. The description does not mention any parameters, their roles, or how they affect output (e.g., pool_id, chain, verbosity). With 6 parameters and no schema documentation, the description fails to add meaning beyond the schema itself.
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 it returns detailed evidence for a pool lookup, listing specific components (APR history, TVL, risk context, follow-up actions). This distinguishes it from sibling tools like get_market_snapshot (market-level data) and get_protocol_security_status (security focus).
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 when pool-level evidence is needed, but provides no explicit guidance on when to use this tool vs. alternatives or prerequisites. It lacks exclusions or context for sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_protocol_security_statusCInspectReturn live security status for a supported protocol.
| Name | Required | Description | Default |
|---|---|---|---|
| protocol | Yes | ||
| verbosity | No | full |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It mentions 'live' but does not explain side effects, authorization requirements, or idempotency. For a tool returning status, it lacks crucial transparency.
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 short sentence with no fluff, but it is under-specified. It earns its place by stating the core function, but could include more detail without adding length.
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 two parameters and an output schema, the description does not explain what 'supported protocol' means or how 'live security status' is defined. It lacks context for effective use, especially compared to sibling tools.
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. It does not explain what values 'protocol' accepts or how 'verbosity' affects output. The tool name implies protocol is a protocol identifier, but without elaboration.
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 uses a specific verb ('Return') and resource ('live security status') with a qualifier ('for a supported protocol'). It clearly distinguishes from sibling tools like 'get_market_snapshot' and 'get_optimal_allocation' which target different domains.
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. The description does not mention prerequisites, exclusions, or contexts where other tools would be preferred.
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.
No comments yet. Be the first to start the discussion!
