agent-staking-mcp-server

by AiAgentKarl

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct operation: dispute opening/resolution, stake deposit/verification/leaderboard/slashing, and reputation scoring. No overlapping or ambiguous purposes.
Naming Consistency4/5
Most tools follow a noun_verb pattern (e.g., stake_deposit, dispute_open) or verb_noun (slash_stake). However, reputation_by_stake deviates with a preposition, and leaderboard is a noun rather than an action.
Tool Count5/5
7 tools cover the core staking and dispute resolution workflows without being too few or excessive. The number feels right for the domain.
Completeness4/5
Core CRUD-like operations are present for staking (deposit, verify, slash) and disputes (open, resolve). Missing are a withdraw/unstake tool and perhaps a dispute list, but these are not essential for basic functionality.
Average 4/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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

Behavior3/5
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 discloses that the defendant's stake is automatically slashed if they lose, and that the description is permanently logged. However, it does not mention authorization requirements, other side effects, or whether the dispute can be canceled.
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 concise and front-loaded with the purpose. Every sentence adds information, though the argument list could be more succinctly integrated.
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 4 parameters, no output schema, and no annotations, the description covers the basic action and one key behavioral effect. It lacks details on return values, error conditions, or prerequisites (e.g., both agents must have stakes).
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 0%, so the description must add meaning. It provides minimal context for each parameter (e.g., 'Agent filing the complaint' for claimant_id, 'What happened (will be permanently logged)' for description). This adds some value but does not fully compensate for the missing schema descriptions.
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 'Open a dispute between two agents.' This is a specific verb+resource combination that distinguishes it from siblings like tool_dispute_resolve, tool_slash_stake, etc.
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 explains a consequence (stake slashing if defendant loses) but does not provide explicit guidance on when to use this tool versus alternatives like tool_dispute_resolve. No exclusions or context are given.
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?
Without annotations, the description adds some transparency by listing factors combined (stake size, slash history, membership duration) and return fields (score, grade, breakdown). However, it does not disclose whether the tool is read-only or has 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences and an args line with no waste. The purpose is front-loaded, and every sentence adds value.
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 single-parameter tool with no output schema, the description adequately covers what the tool returns and the factors used. Minor gap: no details on the breakdown structure.
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 description explains 'agent_id' as 'Agent identifier to evaluate', adding context beyond the schema title. With 0% schema description coverage, this is helpful, but still lacks format or examples.
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 'Get' and the resource 'stake-weighted reputation score', with a specific range (0-100). It distinguishes from sibling tools by focusing on reputation rather than disputes, slashing, or leaderboard.
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 explicit guidance on when to use this tool versus alternatives. The description does not mention when not to use it or compare to siblings like tool_stake_leaderboard, which could provide raw stake data.
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?
No annotations are provided, so the description carries the full burden. It notes that stake can be slashed, adding behavioral context. However, it does not disclose other traits such as whether deposits are additive, idempotent, or require specific auth. The description gives some transparency but lacks depth for a mutation tool.
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, with a clear first sentence stating purpose, followed by tier explanation and a warning about slashing. The structured Args section is efficient. Every sentence adds value without redundancy.
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?
No output schema exists, and the description does not mention what the tool returns (e.g., updated stake, confirmation). While the tool is simple, the lack of return value information leaves a gap. Sibling tools provide some context, but completeness for a deposit operation could be improved.
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 coverage is 0%, but the description adds meaning to all three parameters: agent_id (e.g., DID, UUID, name), amount (>0), and currency (default: REP). This fully compensates for the missing schema documentation, providing essential usage guidance.
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: 'Deposit stake for an agent as a trust proof.' It explains the purpose (increasing trust tier) and distinguishes from sibling tools like slash, verify, and leaderboard by focusing on the deposit action. The verb 'deposit' and resource 'stake' are specific and 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 provides context (higher stake = higher tier) but lacks explicit guidance on when to use this tool versus alternatives like slash or verify. It implies usage for increasing trust but does not state exclusions or prerequisites. The information about tiers and slashing is helpful but not directive.
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?
No annotations provided, so description carries full burden. It explicitly states it is a read-only verification returning balance, trust tier, slash history, and trust score. This clearly indicates no destructive side effects. However, it omits authentication requirements or rate limits.
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?
Description is concise (4 lines), front-loaded with purpose, and includes structured Args block. Every sentence adds value with no extraneous text.
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?
The tool is simple with 1 parameter. Description explains return values (balance, trust tier, etc.) compensating for lack of output schema. However, it could mention that verification is typically a prerequisite for other stake operations, but that overlaps with usage guidelines.
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?
Only one parameter (agent_id). Description adds 'to look up' which is minimal beyond the schema's title and type. With 0% schema description coverage, the description partially compensates but does not provide rich semantic detail like expected format or example.
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 'Verify' and the resource 'agent's stake status and trust level'. It distinguishes from siblings like tool_slash_stake or tool_stake_deposit by focusing on verification rather than mutation or deposits.
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?
No explicit when-to-use or when-not-to-use guidance. The description implies it is for checking status before actions like disputes or slashes, but does not mention alternatives or exclusions. Adequate but lacks proactive guidance.
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?
No annotations are provided, so the description fully bears the burden. It discloses that the tool returns a leaderboard and explains ranking criteria ('Higher stake + no slashes + longer membership = better ranking'). However, it does not mention whether the operation is read-only or any potential side effects, though it is clearly a read operation.
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 (4 lines, two sentences plus an Args section). Every sentence adds value: explains purpose, ranking logic, and parameter. No superfluous content.
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 no output schema, the description could explain the return format (e.g., list of agent names with trust scores or stake amounts). It only describes ranking criteria but not the structure of results. For a simple leaderboard, this is acceptable but leaves some ambiguity.
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 0%, so the description compensates by explaining the single parameter top_n as 'Number of agents to show (default: 10)'. This adds meaning beyond the schema's title and default value.
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 'Get the trust leaderboard — top staked agents ranked by trust score.' It uses a specific verb ('Get') and resource ('trust leaderboard'), and the mention of 'staked agents' and 'trust score' distinguishes it from sibling tools like tool_reputation_by_stake or tool_slash_stake.
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 viewing most trustworthy agents but does not explicitly state when to use this tool versus alternatives like tool_reputation_by_stake. No 'when not to use' guidance is provided, and no alternative tools are named.
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?
No annotations provided, so description carries full burden. It discloses stake slashing behavior and the condition (claimant win). Slight ambiguity in 'optional' vs 'automatic' but overall transparent.
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?
Description is concise (6 lines), front-loaded with main purpose, and uses an Args block for clarity. No unnecessary 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?
Covers the main side effect (stake slashing) but lacks prerequisites like dispute must be open or stakeholder conditions. No output schema, so return values not specified. Slightly incomplete but adequate for a simple tool.
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 0%, so description must add meaning. It explains dispute_id and winner_id clearly, but resolution_notes is minimal. No format or constraints given beyond basic explanations.
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 resolves an open dispute and optionally slashes loser's stake. It specifies the automatic slashing when claimant wins, and distinguishes from sibling tools like tool_dispute_open or tool_slash_stake.
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?
Implies usage after a dispute is opened (via sibling tool_dispute_open) but doesn't explicitly state when to use or not use. No alternatives mentioned, but the context is clear enough for an AI agent.
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?
No annotations are provided, but the description fully discloses key behavioral traits: the slash is permanently recorded in the agent's history and reduces the agent's trust score and tier. This clearly communicates the destructive, irreversible nature of the action, which is critical for an agent deciding to invoke this tool.
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: two sentences for purpose and effects, then a three-line bullet list for arguments. No redundant or irrelevant information. Every sentence adds value, and the structure is clear and scannable.
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 lack of annotations, output schema, and low schema coverage, the description covers the key behavioral effects and parameter meanings. However, it omits details like return value (confirmation message?), error cases, and potential limits on slash_amount. It is adequate but not fully comprehensive for an agent to use without additional context.
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 0%, so the description must compensate. It provides brief explanations for all three parameters (agent_id, slash_amount, reason) beyond their schema titles. However, it does not specify constraints (e.g., slash_amount must be positive, reason max length) or format, leaving some ambiguity for the agent.
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: slashing an agent's stake for bad behavior (fraud, non-delivery, rule violations). It specifies the action (slash) and the resource (agent's stake), and it distinguishes from sibling tools (e.g., stake_deposit, stake_verify) by focusing on punitive 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 lists concrete examples of when to use the tool (fraud, non-delivery, rule violations) and mentions permanent recording and impact on trust score/tier. While it doesn't explicitly say when not to use or name alternatives, it implies usage for punitive actions, which provides sufficient context for selection.
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:

[![agent-staking-mcp-server MCP server](https://glama.ai/mcp/servers/AiAgentKarl/agent-staking-mcp-server/badges/card.svg)](https://glama.ai/mcp/servers/AiAgentKarl/agent-staking-mcp-server)

Score Badge

Copy to your README.md:

[![agent-staking-mcp-server MCP server](https://glama.ai/mcp/servers/AiAgentKarl/agent-staking-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/AiAgentKarl/agent-staking-mcp-server)

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/AiAgentKarl/agent-staking-mcp-server'

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