This is the mcp server of L&T
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 4.6/5 across 1 of 1 tools scored.
Only one tool exists, so there is zero risk of selecting the wrong tool. The tool's description clearly defines its role as the sole gateway.
The single tool name 'discover_tools' follows a consistent verb_noun pattern. There are no other tools to create inconsistency.
One tool is minimal, but intentional for a gateway pattern that dynamically exposes other tools. It is slightly under the typical 3-15 range yet justified by the meta-purpose.
The tool covers both discovery and execution, fully addressing the server's stated purpose. A minor gap is the lack of a way to list all available tools without a query, but query-based discovery is sufficient.
discover_toolsAInspectTwo-step tool finder and executor for all enterprise APIs.
STEP 1 — DISCOVER: Call with only 'query'. Returns matching tools with their names and inputSchemas.
STEP 2 — EXECUTE: Call again with 'query' + 'tool_name' + 'tool_args'. Gateway executes the tool and returns real data directly.
You NEVER call any other tool directly. Always use discover_tools.
| Name | Required | Description | Default |
|---|---|---|---|
| team | No | Optional department filter. | |
| query | Yes | User intent in plain natural language. | |
| top_k | No | Number of tools to return. Default 5, max 10. | |
| tool_args | No | STEP 2 only — arguments matching the tool's inputSchema exactly. Provide together with tool_name to execute the tool. | |
| tool_name | No | STEP 2 only — exact tool name from previous discover response. Must match a name returned in the previous discover call exactly. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on heavy responsibility. It discloses the two-step behavior, what returns in discovery (names and inputSchemas), that execution returns real data directly, and that the tool name must match exactly. It doesn't mention side effects or permissions, but the core behavioral workflow is clearly documented.
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 well organized with clear STEP 1 and STEP 2 markers, using a compact list format. Every sentence adds value, and the critical directive about not calling other tools is prominent. No redundancy or filler is present.
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 (5 params, nested objects, two-phase usage) and lack of an output schema, the description covers the core flow and return values well enough for an agent to invoke it correctly. It does not detail error cases or edge scenarios, but for a tool finder gateway, the described two-step protocol is sufficient for expected use.
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?
Although schema coverage is 100%, the description adds meaningful phase-specific semantics for parameters like 'tool_name' ('exact tool name from previous discover response') and 'tool_args' ('arguments matching the tool's inputSchema exactly'). It clarifies the role of 'query' as user intent and the optional 'team' filter, going beyond mere schema repetition.
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 identifies the tool as a two-step finder and executor for all enterprise APIs, with a specific verb ('discover'/'execute') and resource. It explicitly distinguishes its role by stating that no other tool should be called directly, making it unique even without siblings.
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?
It provides explicit step-by-step usage instructions: STEP 1 for discovery with only 'query', and STEP 2 for execution with 'query' + 'tool_name' + 'tool_args'. It also gives a strong directive ('You NEVER call any other tool directly') that clarifies when to use this tool versus any alternative.
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.
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