FinCore Agentic Commerce
Server Details
Agentic commerce with 58 MCP tools for product search, checkout, A2A negotiation, C-Suite analytics.
- 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 3.8/5 across 2 of 2 tools scored.
The two tools target clearly distinct operations: one retrieves a specific product by ID, the other searches across products with a query. No overlap in purpose.
Both tools follow the consistent verb_noun pattern (get_product, search_products), using lowercase with underscores. No deviation.
With only 2 tools, the server feels overly minimal for a commerce domain. Typically one would expect at least create, update, delete, and possibly cart/order tools.
The tool set lacks essential CRUD operations (no create, update, delete) and covers only read access. Significant gaps exist for a commerce platform, limiting agent capabilities.
Available Tools
2 toolsget_productAInspect
Get product details by ID
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | Product ID |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a read operation ('Get') but does not disclose error handling (e.g., if product not found), authentication needs, or specific details returned. With no annotations, the description is adequate but not rich.
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 with no extraneous information, perfectly 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?
Given the simplicity (1 integer parameter, no output schema, no annotations), the description is minimally complete for a get-by-ID tool, though it could mention return value expectations.
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%, and the description adds no additional meaning beyond what the schema already provides ('Product ID'). Baseline 3 is appropriate.
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 the resource 'product details by ID', distinguishing it from the sibling tool 'search_products' which searches multiple products.
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 (when you need details for a specific product ID) but does not explicitly exclude other scenarios or mention alternatives like 'search_products'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_productsAInspect
Search products in connected WooCommerce stores
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search keyword |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description lacks any behavioral details such as pagination, sorting, result limits, or scope (e.g., returns list of products).
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?
Single sentence with no unnecessary words; front-loaded with purpose.
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 simple tool with one parameter and no output schema, the description is minimally adequate but fails to specify return format or result type (e.g., list of products).
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% with one parameter ('query') described as 'Search keyword'. The description adds no additional meaning beyond the schema, meeting baseline but not exceeding it.
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 'Search' and resource 'products' with scope 'in connected WooCommerce stores', clearly distinguishing from sibling 'get_product' which likely retrieves a single product.
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 vs alternatives; usage is implied but not stated, e.g., 'search broadly vs. get specific product'.
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.
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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
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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
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The server is experiencing an outage
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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.
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