anchor-mcp

by thewillmoss

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation5/5
Each manager tool targets a distinct resource (tasks, plans, notepads, memory, rules), and promote_learning is a clearly separate action that bridges plans and rules. There is no overlap or ambiguity in purpose.
Naming Consistency4/5
Five tools follow a consistent 'X_manager' pattern, but promote_learning breaks the pattern with a verb_noun style. The names are all snake_case and readable, but the one deviation prevents a perfect score.
Tool Count5/5
Six tools is an appropriate size for a project management and knowledge assistant. Each tool covers a clear domain area, and the count feels neither sparse nor overwhelming.
Completeness4/5
The tool surface covers list, read, create/update for five resource types, plus a special promotion action. The main gap is the lack of explicit delete or remove operations for resources, but this is likely a design choice and can be worked around.
Average 3.7/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 21 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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 are provided, so the description carries full responsibility for behavioral disclosure. It only lists actions without detailing side effects (e.g., whether 'add' can overwrite), persistence, permissions, or return behavior. This is a significant gap for a tool with a mutation action.
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 a single sentence, front-loaded with the primary verb 'Manage', and efficiently lists the three actions without redundancy. Every word earns its place; it is appropriately sized for the tool's simplicity.
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 moderate complexity of three actions and complete schema coverage, the description is superficially sufficient. However, it lacks context on action-specific behaviors (e.g., search syntax, list ordering) and has no output schema to clarify return values. It is minimally complete but not rich.
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?
Input schema has 100% parameter description coverage, including enums and conditional requirements (e.g., content required for add, query for search). The description adds no extra parameter information beyond what the schema already 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: managing memory via three specific actions (add, search, list). The resource 'memory' is distinct from sibling tools like task_manager or plan_manager, making its function unambiguous.
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?
The description provides no guidance on when to use this tool vs alternatives. It does not mention sibling tools, prerequisites, or scenarios where this tool is preferred. The usage is only implied by the enumerated actions, but no explicit context is given.
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 carries the full burden of behavioral disclosure. It mentions state-changing operations ('set a new active task', 'complete a task') but does not disclose potential side effects such as overwriting the current active task, irreversibility of completion, or any data loss. It also omits permissions and return value information.
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 a single sentence with a colon-separated list of operations. It is front-loaded with 'Manage tasks' and every word contributes to understanding the tool's scope. No redundancy or filler.
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 four parameters and no output schema, the description provides a high-level overview but lacks operational context such as return formats, side effects, or error conditions. The schema covers parameter details, but the description does not fully compensate for the lack of annotations or output schema.
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 description coverage is 100%, with all parameters having descriptive text and enums for action and status. The description adds no extra semantic detail beyond what the schema already provides, so the baseline score of 3 is appropriate.
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 'Manage tasks' and enumerates four specific operations: get active, set new active, complete, and list. The resource 'tasks' distinguishes it from sibling managers like plan_manager, notepad_manager, and memory_manager, making the purpose unambiguous.
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 for task management but provides no explicit when-to-use guidance, exclusions, or comparisons to alternatives. Unlike the sibling tools, there is no mention of when not to use this tool or when a sibling would be more appropriate.
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 lists the three actions but does not disclose behavioral details such as whether 'save' overwrites existing content, what 'get' returns, or the effect of the 'section' parameter. With no annotations provided, the description carries the full burden of behavioral transparency and falls short.
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 a single concise sentence that front-loads the main purpose and enumerates the three actions efficiently. Every phrase contributes meaning.
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's moderate complexity (multiple actions, no output schema), the description covers the core operations but lacks details on return values and side effects. The schema helps with parameter semantics, but the description could be more complete regarding each action's behavior.
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?
The input schema provides descriptions for all 4 parameters, achieving 100% coverage. The description adds minimal semantic value beyond the schema, but the baseline for high coverage is 3.
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's purpose: managing plans with explicit actions to read, save/update, and list. This distinguishes it from sibling tools focused on other resource types like tasks or memory.
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 gives clear context on when to use this tool by enumerating the supported actions (read, save/update, list) for plans. It doesn't mention alternatives or exclusions, but the resource specificity implies the appropriate use case.
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 provided, so the description carries the full burden. It mentions read and save/update actions but does not disclose side effects of saving (e.g., overwriting existing rules), required permissions, or any consequences of the operations. This leaves significant behavioral ambiguity for an agent.
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 a single, well-structured sentence that front-loads the purpose ('Manage project rules') and then uses a colon to specify the two modes. Every word contributes value, with no redundancy or unnecessary detail.
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's simplicity and 100% schema coverage, the description provides the core purpose and operation modes. However, it lacks explicit usage guidance and behavioral details (like content being required for save), leaving the agent to infer some important context that is only partially available in the schema.
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?
The schema covers both parameters with descriptions, so baseline is 3. The description adds meaning by explaining that 'get' corresponds to 'read current rules' and 'save' to 'save/update rules', which clarifies the purpose of the action enum beyond the schema's generic 'The rules action to perform'.
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 manages project rules, specifying two specific actions: reading current rules and saving/updating rules. This distinguishes it from sibling tools like task_manager and plan_manager, which handle different resources.
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 this tool is for managing rules, but it does not explicitly state when to use it over alternatives or provide any exclusions. The context is clear from the resource name, but no direct guidance is given about choosing between get and save actions or comparing to sibling managers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses the critical mutation behavior by stating it appends to rules.md, which indicates a non-destructive write. However, it omits potential side effects (e.g., duplicate handling), permissions required, or reversibility, leaving gaps in the behavioral picture.
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 and contains no filler. Each phrase adds value: the action, source, destination, and the specific file operation are all stated efficiently. It is perfectly sized for the tool's simplicity.
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 simple two-parameter tool with no output schema, the description adequately covers the essential behavioral contract. It specifies the mutation target and the operation, which is sufficient for an agent to select and invoke the tool. Minor gaps such as error handling or return value are not critical given the tool's straightforward nature.
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?
The schema provides 100% coverage of parameter descriptions: 'planName' is clearly explained, and 'learningIndex' is described as optional with a default behavior. The description itself adds no additional semantic meaning beyond the schema, so it meets the baseline for well-documented parameters.
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 action ('Promote learnings') and the resource ('from a plan into project rules'), and also specifies the concrete outcome ('appends plan learnings to rules.md'). It distinguishes itself from sibling tools by revealing the exact file operation, making the tool's function unambiguous.
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 its use case (promoting learnings from a plan) but provides no explicit guidance on when to choose this tool over alternatives like rules_manager or memory_manager. There are no stated exclusions or conditional use cases, so the guidance remains implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses basic read vs. write behavior ('read' vs. 'save/update') and clarifies that 'save/update' covers both creation and modification. However, it does not detail whether saving overwrites existing content, what return values look like, or any side effects, leaving notable gaps for a tool with no annotation support.
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?
A single sentence, front-loaded with 'Manage notepads' and followed by an explicit enumeration of actions. No filler words, every clause contributes necessary 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 simple 3-parameter tool with no output schema, the description covers the main operations and the topic-based access pattern. It does not specify return formats or error handling, but these are secondary for a basic notepad manager, and sibling tool names make the domain clear.
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?
All three parameters have schema descriptions (100% coverage), so the baseline is 3. The description adds marginal value by mapping actions (read, save/update, list) to the action enum and indicating topic is used for get/save, but this mostly restates schema information without new semantics.
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 names the resource (notepads) and specifies three concrete operations—read by topic, save/update, list topics—making it clear what the tool does. It distinguishes from sibling managers by focusing exclusively on notepads.
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 implies usage: use this tool when you need to read, save/update, or list notepads. It does not explicitly compare to alternatives like task_manager or memory_manager, nor state when not to use it, so it lacks explicit exclusions. However, the context is sufficiently clear for a CRUD tool.
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:

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

Score Badge

Copy to your README.md:

[![anchor-mcp MCP server](https://glama.ai/mcp/servers/thewillmoss/anchor-mcp/badges/score.svg)](https://glama.ai/mcp/servers/thewillmoss/anchor-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/thewillmoss/anchor-mcp'

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