Skip to main content
Glama

M.K. Electronics

Server Details

Live shopping connector for M.K. Electronics — Bangladesh's largest authorized multi-brand electronics retailer (40+ years; 100+ global brands; 16 superstores nationwide). Use the included tools to search the in-stock catalog, fetch full product details with specs and EMI options, list categories, and find showrooms in any city. Returns current pricing in BDT and live availability — no HTML scraping needed. Ideal for shopping assistants helping customers in Bangladesh decide what to buy.

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.

MCP client
Glama
MCP server

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.

100% free. Your data is private.
Tool DescriptionsA

Average 4.3/5 across 4 of 4 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool targets a distinct function: location, product details, category tree, and full-text search. No overlap or ambiguity.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with underscores (find, get, list, search). Minor variation in length but no mixing of conventions.

Tool Count5/5

4 tools cover the essential operations for an electronics store catalog: browsing, searching, details, and store locator. Well-scoped for the domain.

Completeness4/5

Covers core read operations, but lacks direct category-to-product listing or advanced filtering. Minor gap for browsing without prior search.

Available Tools

4 tools
find_showrooms_nearFind showroomsAInspect

List M.K. Electronics showrooms, optionally filtered by city. 16 superstores nationwide.

ParametersJSON Schema
NameRequiredDescriptionDefault
cityNoCity filter, e.g. "Dhaka" or "Chattogram". Omit to list all.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations, but description discloses read-only listing behavior, optional filter, and scope (16 stores). Adequate for a non-destructive tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with no filler. Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple listing tool with one optional parameter and no output schema, the description is complete: purpose, filter, and scale are covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage with description for city parameter. Description adds no extra param details beyond 'optionally filtered by city', meeting baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'List M.K. Electronics showrooms' with optional city filter. Distinct from sibling tools (products/categories).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes optional city filtering and gives scale (16 superstores nationwide). No explicit when-not, 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.

get_productGet product detailsAInspect

Fetch full product detail by slug — specs, EMI options, warranty, current price, stock. Use after search_products when the user wants to dig into one item.

ParametersJSON Schema
NameRequiredDescriptionDefault
slugYesProduct slug from a search result, e.g. "sony-bravia-x90l-65"
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so description carries full burden. It lists what data is returned but does not explicitly state read-only nature or potential errors. However, it effectively conveys the behavior for a standard fetch operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence that front-loads the core purpose and includes key details. Every word adds value; no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, so description explains return values. However, it doesn't mention possible error scenarios (e.g., invalid slug) or authentication. Still, it provides sufficient context for a simple fetch tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers the single parameter with 100% coverage. Description adds value by clarifying the slug's origin ('from a search result') and providing an example. This goes beyond the schema's description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches full product details by slug, listing specific content like specs, EMI options, warranty, price, stock. It distinguishes from sibling tools like search_products by indicating this is for deeper dive.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use after search_products when the user wants to dig into one item.' This provides clear context and guidance on when to invoke this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_categoriesList categoriesAInspect

Get the storefront category tree. Use to orient the user when they're browsing without a specific product in mind.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses the tool returns a 'category tree', but doesn't mention hierarchy depth, caching, auth requirements, or any side effects. It's adequate for a simple read call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, each serving a purpose. Front-loaded with the action. No excessive wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (no parameters, no output schema), the description is complete. It explains purpose and usage. No output schema, but 'category tree' sufficiently describes return.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are 0 parameters and schema coverage is 100%. Per guidelines, baseline is 4. The description doesn't add parameter info, but none needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get the storefront category tree', identifying both the verb and resource. It distinguishes itself from siblings by indicating it's for browsing without a specific product, contrasting with search_products or get_product.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context: 'Use to orient the user when they're browsing without a specific product in mind.' It implies when not to use (when user has a specific product), but doesn't explicitly name alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_productsSearch productsAInspect

Full-text search across the M.K. Electronics catalog. Returns in-stock matches only, ordered by relevance. Use this when the user asks to find / compare / shop for something.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 20, hard cap 50)
queryYesSearch keywords, e.g. "65 inch sony oled" or "inverter ac 1.5 ton"
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that results are in-stock only and ordered by relevance, but does not mention permissions, side effects, rate limits, or any other behavioral traits. Lacks depth for a mutation-agnostic tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loaded with the core functionality, and contains no wasted words. Every sentence provides useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter search tool with no output schema, the description adequately covers purpose, scope, filtering, ordering, and usage context. It could optionally mention the return format (e.g., product IDs) but is otherwise sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds no additional semantics beyond what the schema already provides for the query and limit parameters. The schema includes examples and constraints (e.g., hard cap 50), so the description adds minimal value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs full-text search across the M.K. Electronics catalog, returns in-stock matches ordered by relevance, and specifies when to use it (find/compare/shop). This distinguishes it from siblings like get_product (single product) and list_categories (categories).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this when the user asks to find / compare / shop for something,' giving clear usage guidance. However, it does not mention when not to use it or provide alternative tools, which would be more helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Discussions

No comments yet. Be the first to start the discussion!

Try in Browser

Your Connectors

Sign in to create a connector for this server.

Resources