memtrust
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Only one tool exists, so there is no possibility of confusing it with another. The description clearly explains what `run` does.
Naming Consistency4/5The tool name 'run' is a simple verb without a noun, but since it is the only tool, there are no conflicting conventions. It follows a typical CLI command pattern.
Tool Count3/5With just a single tool, the server feels thin and offers only one entry point. However, given the server's narrow purpose of running a benchmark harness, the count might be justified.
Completeness5/5The tool fully covers the server's purpose: running the memtrust benchmark with customizable args and handling missing backend credentials gracefully. No obvious missing operations.
Average 4.4/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 111 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
This server has been verified by its author.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states that the tool returns a JSON report, passes args straight through to `memtrust run`, and that backends without credential env vars are reported as skipped rather than errors. These are useful behavioral traits that go beyond a simple command wrapper. It could mention side effects, but for a benchmark runner this is adequately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the main action stated first. It includes a helpful example and a behavioral note. The inclusion of the real `memtrust --help` output adds some extra length, but it is brief and provides relevant context. No sentence is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool, the description covers the essential aspects: what it does, how the parameter works, and the handling of missing credentials. An output schema exists, so return values are already specified elsewhere. The description is complete enough for the agent to invoke the tool correctly with minimal ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero description coverage for the `args` parameter, so the description must compensate. It does so explicitly: '`args` are passed straight through to `memtrust run`' with an example. This fully explains the meaning and format of the parameter, which is the only one. This is exemplary compensation for a poorly documented schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Run the memtrust agent-memory benchmark harness and return the resulting JSON report.' It specifies the verb (run) and the resource (the benchmark harness), making the purpose unambiguous. Even without sibling tools, the description is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: to run the memtrust benchmark harness. It also explains how the args are passed through and gives an example, which serves as implicit usage guidance. While there are no exclusions or alternative tools to differentiate from, the provided context is sufficient for the agent to decide when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/RudrenduPaul/memtrust'
If you have feedback or need assistance with the MCP directory API, please join our Discord server