klanex
Server Details
Reliable async execution for agent tool calls: schema gating, retries, idempotency, audit trail.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- chrassy/klanex-mcp
- GitHub Stars
- 0
- Server Listing
- klanex-mcp
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.4/5 across 6 of 6 tools scored.
Each tool has a clearly distinct purpose: execute, get_execution, get_usage, list_connections, list_executions, replay_execution. No overlapping functionality; descriptions clearly differentiate them.
All tools follow a consistent verb_noun pattern (execute, get_execution, get_usage, list_connections, list_executions, replay_execution). Naming is uniform and predictable.
Six tools cover the core functionality of an execution management server: initiating, checking, listing, replaying executions, plus managing connections and usage. This is well-scoped, not too few nor too many.
The tool set provides a complete lifecycle for asynchronous API execution: create (execute), check status (get_execution), list (list_executions), replay (replay_execution), manage credentials (list_connections), and monitor usage (get_usage). No obvious gaps for the stated domain.
Available Tools
6 toolsexecuteAInspect
Submit an HTTP call to a third-party API for reliable asynchronous execution. klanex validates the payload (optionally against payload_schema), stores credentials encrypted, executes with automatic retries/backoff/circuit breakers, and keeps an audit trail — you submit once and never retry transient failures yourself.
Call this instead of making a direct HTTP request whenever the call has side effects (payments, messages, tickets, writes) or the target may be flaky. Prefer connection_id over headers for credentials. Always set idempotency_key for side-effecting calls so resubmitting can never double-execute. Set wait_seconds to block for the result; otherwise poll get_execution with the returned execution_id.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | absolute http(s) URL of the target endpoint | |
| method | No | HTTP method: GET, POST, PUT, PATCH, or DELETE (default POST) | |
| headers | No | request headers, typically third-party credentials; encrypted at rest and never readable back. Prefer connection_id so secrets never pass through your context | |
| payload | No | JSON body to send to the target | |
| seal_url | No | set true when the URL itself is a secret (webhook URL, presigned URL); it is encrypted and reads back redacted | |
| timeout_ms | No | per-attempt timeout in milliseconds (default 30000) | |
| max_attempts | No | maximum delivery attempts, 1-10 (default 5) | |
| wait_seconds | No | block up to this many seconds (max 55) for a terminal result instead of returning immediately after queueing | |
| connection_id | No | ID of a stored credential connection (con_...) to authenticate the call; see list_connections | |
| payload_schema | No | JSON Schema to validate payload against before anything executes; mismatches are rejected synchronously with a correction hint | |
| idempotency_key | No | stable key (max 255 chars) making this submit safe to retry; the same key returns the original execution instead of creating a new one. Always set this for side-effecting calls | |
| requires_approval | No | pause for a human approve/reject decision before anything executes; use for destructive or high-stakes actions |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description thoroughly discloses behavior: validation against payload_schema, encrypted credential storage, automatic retries/backoff/circuit breakers, audit trail, idempotency (idempotency_key prevents double execution), and blocking option (wait_seconds). It also explains that you never need to retry transient failures. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized, front-loaded with the purpose, and each sentence adds value. It is structured with a summary followed by actionable guidance, avoiding redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 parameters, no annotations, no output schema), the description is quite complete. It covers when to use, behavioral traits, parameter usage, and the return implication (execution_id for polling). Lacks explicit return structure but compensates with polling guidance. Could be slightly more detailed on error responses, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaningful usage guidance beyond schema: e.g., 'prefer connection_id so secrets never pass through your context' and 'Always set idempotency_key for side-effecting calls so resubmitting can never double-execute.' This extra context justifies a score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool submits an HTTP call to a third-party API for reliable asynchronous execution. It uses specific verbs ('submit') and identifies the resource ('HTTP call'), and distinguishes itself from direct HTTP requests by emphasizing reliability and side-effect handling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool: 'whenever the call has side effects (payments, messages, tickets, writes) or the target may be flaky.' Also provides clear directives: prefer connection_id, always set idempotency_key for side-effecting calls, and set wait_seconds or poll get_execution. No alternative tool confusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_executionAInspect
Fetch the current state of an execution by ID: status (PENDING_APPROVAL|QUEUED|RUNNING|RETRYING|SUCCEEDED|FAILED), attempts, the target response on success, or a classified error on failure. Retryable failures need no action from you — klanex is still retrying. Header values always read back REDACTED.
| Name | Required | Description | Default |
|---|---|---|---|
| execution_id | Yes | the execution ID (exe_...) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that header values are always redacted and explains retry behavior. Lacks mention of permissions or side effects, but as a fetch operation, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with purpose. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema but description explains return fields. Sufficient for a simple fetch tool; no missing details needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds minimal value beyond confirming the ID format (exe_...). Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it fetches the current state of an execution by ID, listing specific fields. Distinguished from siblings like execute, list_executions, and replay_execution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides implicit usage guidance: use when you need execution state. Explicitly notes that retryable failures require no action, which guides agent behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_usageAInspect
Report the account's plan and execution usage for the current calendar month: used, included_executions, remaining, and whether overage is allowed. Check this before large batches to avoid hitting a hard quota.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It describes the report's output (usage fields) but does not explicitly state it is a safe read operation, nor mention any side effects or access requirements. Adequate but could be improved with safety clarification.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy. Purpose is stated first, followed by actionable usage advice. Every sentence contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with no output schema, the description covers purpose and usage context adequately. Could mention output format, but not essential for tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters require description, and schema coverage is 100% trivially. With zero parameters, the description adds no parameter info, which is acceptable. Baseline of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reports account usage metrics (used, included_executions, remaining, overage) for the current calendar month, with a specific verb ('Report') and resource, distinguishing it from siblings like execute or list_executions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context ('Check this before large batches to avoid hitting a hard quota'), giving clear when-to-use guidance. Lacks explicit when-not-to-use or alternatives, but the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_connectionsAInspect
List the account's stored credential connections (token vault). Reference a ready connection by its ID in execute's connection_id instead of passing raw headers — the credential is injected at execution time and never passes through your context. Secrets are never returned.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It reveals that credentials are injected at execution time and secrets are never returned, which are key behavioral traits. However, it omits authentication requirements for the tool itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with the main action first. Every sentence adds value: defining the resource, explaining usage with execute, and noting security.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description covers the essential information: what it does, how it relates to execute, and security. Minor omissions like pagination are acceptable for such a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters and 100% schema coverage, no additional parameter semantics are needed. Baseline score of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists stored credential connections. It distinguishes from siblings like execute and list_executions by specifying its purpose of providing a token vault.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains the tool's role in providing connections for execute's connection_id and notes that secrets are never returned. It gives context for when to use it, but does not explicitly mention scenarios where it should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_executionsAInspect
List this account's executions, newest first, optionally filtered by status or a created_at time range. Returns next_cursor when a page is full; pass it back as cursor for the next page.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | page size, 1-100 (default 20) | |
| since | No | only executions created at or after this RFC3339 timestamp | |
| until | No | only executions created before this RFC3339 timestamp | |
| cursor | No | opaque next_cursor value from a previous page | |
| status | No | filter by status: QUEUED, RUNNING, RETRYING, SUCCEEDED, or FAILED |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses ordering (newest first), filtering options, and pagination behavior (next_cursor). No side effects are mentioned, but none are expected for a read-only list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each with a clear purpose. First sentence covers action and filters, second covers pagination. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the tool's behavior for an AI agent to use it correctly. No output schema is provided, but pagination and filtering are well explained. It implicitly returns a list; could be more explicit about the response shape.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds value by explaining pagination (cursor) and ordering (newest first), providing context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'List this account's executions, newest first' and mentions optional filtering by status or time range. It clearly distinguishes from sibling tools like get_execution (single execution) and replay_execution (replay).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the main use (listing executions) and pagination. While it does not explicitly state when not to use or list alternatives, the context is clear enough given sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
replay_executionAInspect
Re-run a terminal (SUCCEEDED or FAILED) execution as a brand-new execution: same target, byte-exact original payload, same sealed credentials, fresh attempt counter. This is the outage-recovery path — failed calls can be re-executed without regenerating the payload. Each call creates a new execution (deliberately not idempotent).
| Name | Required | Description | Default |
|---|---|---|---|
| execution_id | Yes | the execution ID (exe_...) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, description carries full burden. It discloses that a new execution is created, same payload and credentials, fresh attempt counter. Lacks auth/rate limit details but sufficient for most agents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with main action, no redundant information. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Completeness is good for a single-parameter tool with no output schema. Explains purpose, behavior, and non-idempotent nature. Could mention return value (new execution ID) but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with execution_id already described. Description adds context about the tool's behavior but not new parameter semantics. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb ('Re-run') and resource ('terminal execution'), clarifies scope (SUCCEEDED or FAILED), and distinguishes from siblings like 'execute' (fresh execution) and 'get_execution' (read-only).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states this is the 'outage-recovery path' and warns that each call creates a new execution (not idempotent). Implies when to use but does not explicitly list alternatives or when-not conditions.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
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Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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