A
licenseA
qualityB
maintenanceAn MCP server that exposes e18e module replacement data. It helps AI assistants suggest lighter, faster, or native alternatives to common JavaScript/Node.js packages.
2
15
1
MIT
e18e
by dev.e18e
Server Details
The official e18e MCP server keeping your agent in check from installing bloated dependencies.
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- e18e/mcp
- GitHub Stars
- 0
Available Tools
3 toolscode-checkerCheck if the code contains some inefficient or outdated packages imported and suggests alternatives.CInspect
Check if the code contains some inefficient or outdated packages imported and suggests alternatives.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The code to check. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| suggestions | Yes |
TDQS
C2.4/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden for behavioral transparency. It only states the tool checks and suggests alternatives, but lacks details on whether it modifies code, the format of suggestions, or any side effects. This is insufficient for an agent to understand its behavior fully.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant information. However, it could be slightly more structured (e.g., listing actions) without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (though not provided in context), the description may not need to detail return values. However, it lacks clarity on what constitutes 'inefficient or outdated packages' and the nature of the suggestions. The description is adequate but minimal.
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% as the single parameter 'code' has a description. The tool description adds no additional meaning beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus its siblings. There is no mention of context, prerequisites, or when not to use it, leaving the agent to infer usage without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lookup-replacementCheck if a package has a more performant, maintained or efficient replacement by package name, replacement text, or topic. Returns a list of suggestions with descriptions and documentation links.CInspect
Check if a package has a more performant, maintained or efficient replacement by package name, replacement text, or topic. Returns a list of suggestions with descriptions and documentation links.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The package name, replacement text, or topic to search for, e.g. `chalk`, `filter`, or `Array.prototype.map`. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| results | Yes |
TDQS
C2.9/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description bears full burden. It mentions returning a list of suggestions with descriptions and links, but lacks details on side effects, rate limits, or performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that front-load key information. Some redundancy exists between the two sentences (both mention returning a list). Could be slightly tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with output schema, the description covers basic functionality and output. Lacks usage context or error conditions, which would be helpful for completeness.
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% with a detailed description and examples. The tool description merely restates the parameter purpose without adding new semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when seeking better package alternatives, but gives no explicit guidance on when not to use or how it compares to sibling tools 'code-checker' and 'npm-i-checker'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
npm-i-checkerCheck for outdated or insecure npm packages in an install script like `npm i` or `pnpm add` or `yarn add` or `bun i`.BInspect
Check for outdated or insecure npm packages in an install script like npm i or pnpm add or yarn add or bun i.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| command | Yes | The install command to check, e.g. `npm i express lodash` or `pnpm add express lodash` or `yarn add express lodash` or `bun i express lodash`. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| suggestions | Yes |
TDQS
B3.1/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It states the tool checks for outdated or insecure packages, which implies a read-only analysis, but does not detail side effects, output format, or failure behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the purpose, though it repeats the parameter examples. It is concise but could be slightly tighter.
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?
The tool has an output schema, so return values are covered. The description explains the purpose and usage adequately for a simple check tool, though it could mention what happens when packages are outdated.
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% and the parameter description already includes examples. The tool description repeats these examples without adding new semantics, so it adds marginal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
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 indicates when to use the tool (for install commands like npm i, pnpm add, etc.), but does not explicitly state when not to use it or mention alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
- Added
lookup-replacement
2 tool updates
- First observed
code-checker - First observed
npm-i-checker
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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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TDQS
B3/5.0
Disambiguation4/5
Each tool has a distinct purpose: one checks source code for inefficient imports, one looks up replacements by various criteria, and one checks install command syntax for outdated packages. There is minor overlap between code-checker and npm-i-checker, but descriptions clarify the different contexts, so agents can generally distinguish them.
Naming Consistency3/5
All use snake_case, but the naming patterns are inconsistent: 'code-checker' and 'npm-i-checker' follow a noun-checker pattern, while 'lookup-replacement' uses a verb-noun pattern. 'npm-i-checker' is also somewhat cryptic, mixing package manager syntax. This lack of a uniform verb_noun convention makes the set less predictable.
Tool Count5/5
With 3 tools, the server is well-scoped for its purpose of checking code and packages for inefficient or outdated dependencies. Each tool addresses a distinct aspect of the workflow, and there are no redundant or missing tools that would make the count feel too thin or heavy.
Completeness4/5
The tool surface covers the main needs: checking source code, looking up replacements generally, and verifying install commands. A minor gap is the lack of a direct tool to check a package.json file or to analyze a whole project for inefficiencies, but the three tools together handle most common scenarios without significant dead ends.