tafsiri-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation4/5
Each tool targets a distinct language or concept (Swahili terminology, Kikuyu guide, Luo guide, language detection, document glossary, English-Swahili glossary). Minor overlap between the two Swahili-focused tools but descriptions differentiate them.
Naming Consistency5/5
All names follow a consistent lowercase_with_underscores pattern, combining nouns clearly (e.g., civic_terminology_swahili, language_detection_guide). No mixed conventions.
Tool Count5/5
Six tools cover major Kenyan languages and document types without being excessive. The count is well-scoped for a language resource server.
Completeness3/5
The set provides guides and glossaries for Swahili, Kikuyu, Luo, and official documents, but lacks other Kenyan languages and actual translation functionality. The server's DEMO nature explains the gaps but they are notable.
Average 2.3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 34 commits in the last 12 weeks
- Last stable release on July 18, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
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.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description provides no behavioral traits. It fails to disclose whether the tool is read-only, requires authentication, or handles null inputs. The 'DEMO' suffix hints at limitations but is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (6 words), but it is under-specified rather than concise. It lacks structure and forces the agent to guess the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple schema (1 optional param), no annotations, and existing output schema, the description is woefully incomplete. It does not explain input/output behavior or how this tool differs from similar glossary tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'process' has 0% schema description coverage, and the tool description adds no meaning to it. The purpose and format of the parameter are completely undefined.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Swahili translations of Kenya civic and legal processes' which identifies the domain but lacks a verb specifying the action (e.g., 'get', 'translate'). It partially distinguishes from siblings by mentioning civic/legal focus, but 'DEMO' adds ambiguity about production readiness.
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 on when to use this tool versus siblings like 'swahili_english_glossary' or 'kikuyu_language_guide'. The description does not provide context for appropriate use or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It mentions 'DEMO' which suggests limited functionality, but does not disclose what actions occur (e.g., retrieves information), whether results are cached, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is under-specified given the tool's purpose. It omits essential details while being terse, not concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description fails to explain what the tool returns or how to use the 'term' parameter. Sibling tool names suggest thematic overlap, but no differentiation is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one optional parameter 'term' with 0% description coverage. The description does not explain its purpose (e.g., a word or phrase to look up), expected format, or behavior when omitted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Luo language basics and resources for Kenya. DEMO.' indicates the tool is about the Luo language, but lacks a specific verb or action (e.g., provide, translate, explain). It does not distinguish from sibling language guides like kikuyu_language_guide.
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 alternatives such as swahili_english_glossary or civic_terminology_swahili. The description does not mention context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions 'DEMO' which hints at limited functionality but is not explicit. No disclosure of behavior like querying or returning results.
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, concise and front-loaded with the key topic. However, the 'DEMO' tag is extraneous but not overly damaging.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one optional parameter and no required fields, the description should at least specify what the tool returns. It fails to provide enough context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the 'document_type' parameter's purpose or expected values. The description adds no meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it is a 'terminology guide' for Kenya official documents, which gives a general idea but lacks a specific action verb. It is distinguishable from siblings by domain, but the purpose is vague.
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 on when to use this tool compared to siblings. No indication of contexts or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only states it's a demo, failing to mention whether it is read-only, requires authentication, or has any side effects. This is insufficient for a reliable agent invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short but includes the purpose and demo indicator. However, it lacks detail needed for effective use, balancing conciseness with insufficient information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one optional parameter) and presence of an output schema, the description should explain the tool's return value or behavior. It does not, leaving the agent without crucial context for interpreting results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'term' is not described at all in the description. Schema coverage is 0%, and the description offers no clue about what values to provide or their effect, making it nearly impossible for an agent to use correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool covers Kikuyu language basics and resources for Kenya, and it distinguishes from sibling tools like luo_language_guide and swahili_english_glossary by specifying the language. The 'DEMO' tag indicates it's a demonstration tool.
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 alternatives. It does not mention prerequisites or typical use cases, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description labels the tool as 'DEMO', indicating incomplete functionality, and as a 'Guide', implying read-only behavior. However, with no annotations, it fails to disclose any side effects, permissions, or further behavioral traits such as what happens when 'text_sample' is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, but it is too sparse to be considered effectively concise. While it avoids verbosity, it sacrifices necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 and one optional parameter, the description should clarify what the guide covers, how the input affects the output, and the significance of the 'DEMO' label. It fails to provide sufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not mention the single parameter 'text_sample' at all, providing no guidance on its purpose or format. The description adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it is a guide to language detection and translation for Kenya, which is somewhat clear but vague. It distinguishes from sibling language-specific guides like 'kikuyu_language_guide' by being a general resource, but lacks specificity about what the tool actually does.
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 siblings. The description does not mention use cases, prerequisites, or alternatives, leaving the agent without contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'glossary. DEMO.' It does not reveal whether it is read-only, what happens on misses, or any error behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two words plus 'DEMO'), which is concise but at the cost of essential information. It front-loads the domain but lacks functional detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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, the description fails to explain what the tool returns (e.g., definitions, translations). It does not cover expected behavior or limitations, making it incomplete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'term' has no description in the schema (0% coverage), and the description adds no extra meaning beyond 'glossary.' The usage of 'term' as query or exact match is implied but not clarified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it's a 'Swahili-English civic and government glossary,' clearly indicating the domain and languages. However, it doesn't specify the exact action (e.g., lookup, list) provided by the tool. The DEMO label hints at limitations.
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 information on when to use this tool versus siblings like 'civic_terminology_swahili' or other language guides. There is no context about prerequisites or typical use cases.
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:

[![tafsiri-mcp MCP server](https://glama.ai/mcp/servers/gabrielmahia/tafsiri-mcp/badges/card.svg)](https://glama.ai/mcp/servers/gabrielmahia/tafsiri-mcp)

Score Badge

Copy to your README.md:

[![tafsiri-mcp MCP server](https://glama.ai/mcp/servers/gabrielmahia/tafsiri-mcp/badges/score.svg)](https://glama.ai/mcp/servers/gabrielmahia/tafsiri-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/gabrielmahia/tafsiri-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server