pii-redact
Server Details
Detects and redacts PII (emails, phones, SSNs, names, addresses) from text. $0.01/call via x402.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4/5 across 1 of 1 tools scored.
With only one tool, there is no risk of confusion between tools. The tool's purpose is clearly defined and distinct.
The single tool name 'redact' is clear and follows a straightforward verb pattern. No inconsistency issues.
Having only one tool is borderline; the tool covers both text and JSON PII redaction, but might benefit from separate detection/redaction or input-specific tools.
The tool handles detection and redaction of PII in both text and JSON, covering the core domain. Minor gaps like custom pattern support or a detect-only mode are absent.
Available Tools
1 toolredactAInspect
Detect and redact PII in text or JSON. Recognizers are pure pattern/checksum matching (regex + Luhn/mod-97/SSN-area validation) — no LLM calls, no external services. Person names and dates of birth are matched only via nearby context (e.g. 'Mr. Smith', 'DOB: ...'), not general NER, to keep false positives low.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | ||
| options | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fully discloses the recognizer mechanism (pure pattern/checksum, no LLM/external calls) and details how context-dependent entities (person names, dates of birth) are matched, including intent to keep false positives low. This exceeds typical behavioral disclosure, especially with no annotations.
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 three sentences, each adding essential information: purpose, mechanism, and nuance. There is no redundancy or fluff; it is front-loaded with the core function.
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?
Without an output schema or annotations, the description covers the tool's behavior and intent well but omits return format (e.g., the redacted output structure) and does not elaborate on the options parameter. It is moderately complete for a tool of this complexity.
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?
With 0% schema description coverage, the burden is on the description. It only indirectly mentions entity types (e.g., person names, DOB) but does not explain the 'input' or 'options' parameters, their format, or usage. The description adds minimal semantic value beyond the schema.
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 tool detects and redacts PII in text or JSON, specifying the recognizer type (regex + checksum) and distinguishing it from LLM-based or API approaches. This provides a clear verb+resource and differentiates from potential 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?
The description implies the tool is for deterministic pattern-based redaction, but does not explicitly state when to use it versus alternatives or provide exclusions. The mechanism is explained, but no guidance on context or prerequisites.
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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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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