handoff-mcp

by kirill-sviridov

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.4.0
Disambiguation5/5
Each tool has a clearly distinct purpose: checkpoint ends sessions, consolidates compresses old sessions, get_brief loads the brief, log_event records progress, note_entity stores durable knowledge, search_memory searches across projects, and sync synchronizes with git. No overlap in functionality.
Naming Consistency5/5
All tool names use a consistent snake_case pattern (e.g., get_brief, log_event, note_entity), which is predictable and easy to understand. No mixing of styles.
Tool Count5/5
7 tools is well-scoped for the server's purpose of managing handoff briefs and memory. Each tool covers a necessary operation without being excessive or insufficient.
Completeness5/5
The tool set covers the full lifecycle: starting a session (get_brief), recording progress (log_event, note_entity), searching memory (search_memory), ending sessions (checkpoint), compressing old sessions (consolidate), and syncing (sync). No obvious gaps.
Average 4.7/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 commits in the last 12 weeks
- Last stable release on July 11, 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.
This repository includes a glama.json configuration file.
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.
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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?
Annotations already indicate destructiveHint: true. The description adds operational details: it 'distils old sessions into durable entity notes and archives the originals', clarifying the destructive nature. It also reveals the LLM requirement, which is beyond annotations.
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 very concise: three sentences, no redundancy. Purpose is front-loaded; each sentence adds value: what it does, when to use it, and a key requirement.
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?
Given the tool's complexity (two optional parameters, output schema present), the description covers purpose, usage scenario, and a critical dependency. It does not describe return value but an output schema exists. Some details about parameter defaults (current project) are implied but not explicit.
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%, so baseline is 3. The description does not add significant meaning beyond what the schema already provides for the two optional parameters (project and older_than_days). It mentions 'old finished sessions' but does not elaborate on parameter usage.
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 compresses old finished sessions into durable entity notes, using a specific verb and resource. It distinguishes itself from sibling tools (checkpoint, get_brief, etc.) by being the only one focused on consolidation.
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?
It explicitly tells when to use the tool: when a project's session log is large and space needs to be reclaimed. It also mentions a prerequisite (requires configured LLM model). However, it does not explicitly state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond the annotations: it reveals that checkpointing closes the session, finalizes the note, and returns a brief for the next session. It also warns about the project matching requirement, which is a critical behavioral detail not present in annotations. No contradiction with annotations (idempotent, not read-only, not destructive).
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 highly concise: three sentences that front-load the purpose, then add usage timing and outcome. Every sentence adds value, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but indicated), the description does not need to detail return values. It covers the tool's core function, usage context, and a critical warning about project matching. This is sufficient for an AI agent to decide when and how to invoke it correctly.
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 has 100% description coverage, so the schema already defines parameter meanings. The main description does not add parameter information beyond the schema. According to guidelines, baseline is 3 when coverage is high, and the description does not improve upon the schema's parameter 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 clearly states the tool's operation: 'Close out the current session and produce its hand-off brief.' It uses a specific verb ('close out') and resource ('current session'), and distinguishes from siblings like 'log_event' and 'get_brief' by explicitly marking it as an end-of-session action.
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 provides clear context: 'Call this at the END of a session, or when the user signals they're stopping or switching context.' It explains what happens ('finalises the session note and returns the brief'), but does not explicitly list when not to use it or contrast with sibling tools like 'get_brief' or 'consolidate'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate a non-read-only, non-idempotent, non-destructive tool. The description adds behavioral context beyond annotations: it returns the new event id, and if 'supersedes_query' is used, it reports which prior event was retired. It also notes that superseded events are excluded from future briefs, providing transparency about 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately long (200+ words) but well-structured into paragraphs that front-load the purpose and then detail usage guidelines and return behavior. Every sentence adds value, though some minor redundancy could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, 2 required, output schema), the description fully covers when to use, how to use (atomic, concise, inline links), return values (event id, optional retirement note), and the lifecycle of events (superseding, budget filtering). No gaps identified.
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?
Schema description coverage is 100%, with each parameter well-described. The description adds high-level guidance beyond schema: e.g., 'atomic and concise', 'reference durable notes inline as [[Entity]]', and explains the interplay between 'supersedes' and 'supersedes_query'. This extra context justifies a score above the baseline 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: 'Record a progress signal for the current work session.' It specifies the verb 'Record' and the resource 'progress signal', and distinguishes from sibling tools like 'checkpoint' and 'note_entity' by detailing the exact types of events to log (goal, decision, dead-end, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides extensive guidance on when to use: 'proactively as work happens' with specific triggers (goal changes, decisions, dead-ends, file touches, questions, next steps). It also explicitly advises how to NOT use the tool: 'Keep each event ATOMIC and concise', 'not a multi-paragraph session summary'. This helps the agent decide between this tool and others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false and destructiveHint=false. The description adds that notes are linked via wiki-links and returns the entity name, which are useful behavioral traits beyond annotations. Could be improved by noting if notes are overwritten, but overall good.
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?
Two sentences plus an example list, front-loaded with purpose. No unnecessary words; every sentence adds 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?
Given the rich schema and annotations, the description is nearly complete. It clearly explains the tool's purpose, usage, parameters, and return value. Minor gap: does not specify whether existing notes are updated or appended, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds value by explaining that 'name' becomes a wiki-link target and providing examples, and 'content' is a durable fact. It also clarifies the default for 'project'.
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 verb and resource: 'Record durable, long-lived project knowledge on an entity note.' It also distinguishes from the sibling 'log_event' by specifying use for facts that outlive a single session, and mentions wiki-links and knowledge graph for added clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool vs 'log_event': 'Use this (rather than log_event) for facts that outlive a single session' and provides concrete examples like architecture, conventions, etc.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true (safe, non-destructive). Description adds that the brief is curated, omits retracted decisions, and is not a raw context dump – giving the agent clear expectations about the content. No contradictions with annotations.
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?
Extremely concise, front-loaded with the core purpose. Every sentence serves a purpose: what it does, when to call it, what it contains, and clarifying it's curated. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but indicated), the description doesn't need to detail return format. It covers all relevant aspects: project focus, content summary, and exclusion of raw dumps. Sibling tools are distinct, so no missing comparisons.
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?
Schema coverage is 100% (baseline 3). Description adds semantics for token_budget: 'lowest-priority items drop first', explaining behavior beyond the schema's 'Max tokens'. Also notes project defaults to current project, though schema already says default null. Slight value over baseline.
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?
Description clearly states it 'Load the prioritised hand-off brief for a project' and explains what the brief contains (goal, next step, key decisions, etc.). Distinguishes from sibling tools, none of which serve this specific session-start function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call at the 'START of a session, before doing anything else'. Provides clear when-to-use context and implicitly advises against using it mid-session.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=false, which match the read-only search behavior. The description adds context about return structure (project, content, id) and a usage tip (id can be fed into log_event's supersedes), enhancing transparency beyond annotations.
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 concise yet comprehensive. It starts with a clear purpose, then lists use cases, parameter guidance, and output details—all in a few sentences without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (searching multiple sessions/projects), the description covers when, how, and what to expect, plus a practical usage tip. With an output schema present, the description need not detail return schema, but it adds value explaining the id's role.
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?
Schema description coverage is 100%, so baseline is 3. However, the description adds valuable context beyond schema: explaining scope meaning in context and how the returned id can be reused, providing extra semantic help.
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 'Search memory across sessions and projects,' with a specific verb and resource. It distinguishes this tool from siblings like 'log_event' or 'checkpoint' as the only search tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to call (user references past work) with concrete examples. It explains the 'scope' parameter options and their use cases, helping the agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses all behaviors: returns setup instructions if not configured, otherwise pulls remote work, commits local changes, and pushes. No contradiction with annotations (idempotentHint=true aligns with 'Safe to call repeatedly').
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?
Three sentences, front-loaded with main purpose, then usage and edge cases. No waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully covers setup and normal operation; output schema handles return value details. Adequate for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage for the single parameter remote_url, and description elaborates on its first-time-only usage and default behavior when omitted.
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?
Clear verb 'Sync' with specific resource 'memory vault with private git remote'. Uniquely distinguishable from sibling tools that perform different actions like checkpoint, consolidate, or search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'when the user wants their memory on another device, or to push/pull now.' Also provides setup instructions and notes that it's safe to call repeatedly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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