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0xteamhq

Grafana MCP Server

by 0xteamhq

find_error_pattern_logs

Search Loki logs to identify elevated error patterns within specified time ranges and label scopes for monitoring analysis.

Instructions

Searches Loki logs for elevated error patterns and returns the results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoEnd time for the investigation
labelsYesLabels to scope the analysis
nameYesThe name of the investigation
startNoStart time for the investigation

Implementation Reference

  • The main handler function that creates a Sift investigation of type 'error_patterns' to find elevated error patterns in Loki logs.
    handler: async (params, context: ToolContext) => {
      try {
        const client = createSiftClient(context.config.grafanaConfig);
        
        // Create investigation
        const investigationData = {
          name: params.name,
          start: params.start || new Date(Date.now() - 30 * 60 * 1000).toISOString(),
          end: params.end || new Date().toISOString(),
          labels: params.labels,
          analyses: [
            {
              type: 'error_patterns',
              parameters: {
                labels: params.labels,
              },
            },
          ],
        };
        
        const response = await client.post('/api/v1/investigations', investigationData);
        const investigationId = response.data.id;
        
        // Poll for results (simplified - real implementation would need proper polling)
        await new Promise(resolve => setTimeout(resolve, 5000));
        
        const resultResponse = await client.get(`/api/v1/investigations/${investigationId}`);
        
        return createToolResult({
          investigationId,
          status: resultResponse.data.status,
          analyses: resultResponse.data.analyses,
          message: 'Investigation started. Check status for results.',
        });
      } catch (error: any) {
        return createErrorResult(error.response?.data?.message || error.message);
      }
    },
  • Zod input schema defining parameters: name, labels, optional start and end times.
    const FindErrorPatternLogsSchema = z.object({
      name: z.string().describe('The name of the investigation'),
      labels: z.record(z.string()).describe('Labels to scope the analysis'),
      start: z.string().optional().describe('Start time for the investigation'),
      end: z.string().optional().describe('End time for the investigation'),
    });
  • Registers the findErrorPatternLogs tool within the registerSiftTools function.
    server.registerTool(findErrorPatternLogs);
  • src/cli.ts:126-126 (registration)
    Invokes registerSiftTools (which registers find_error_pattern_logs) if 'sift' tool category is enabled.
    registerSiftTools(server);
  • Helper function to create Axios client for Sift API calls, used by the handler.
    function createSiftClient(config: any) {
      const headers: any = {
        'User-Agent': 'mcp-grafana/1.0.0',
        'Content-Type': 'application/json',
      };
      
      if (config.serviceAccountToken) {
        headers['Authorization'] = `Bearer ${config.serviceAccountToken}`;
      } else if (config.apiKey) {
        headers['Authorization'] = `Bearer ${config.apiKey}`;
      }
      
      // Sift uses a different base URL pattern
      const baseUrl = config.url.replace(/\/$/, '');
      const siftUrl = baseUrl.includes('grafana.net') 
        ? baseUrl.replace('grafana.net', 'sift.grafana.net')
        : `${baseUrl}/api/plugins/grafana-sift-app/resources`;
      
      return axios.create({
        baseURL: siftUrl,
        headers,
        timeout: 60000, // Longer timeout for investigations
      });
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions 'returns the results' but doesn't disclose format, pagination, rate limits, permissions, or what 'elevated error patterns' entails. This is inadequate for a search tool with potential complexity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It avoids redundancy but could be slightly more informative without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on result format, error handling, or behavioral traits, leaving significant gaps for an AI agent to operate effectively.

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%, so parameters are documented in the schema. The description adds no additional meaning about parameters like 'labels' or time ranges, nor does it explain how 'name' relates to the investigation. Baseline 3 is appropriate as the schema handles documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('searches') and resource ('Loki logs') with the specific goal of finding 'elevated error patterns'. It distinguishes itself from generic log query tools like 'query_loki_logs' by focusing on error pattern analysis, though it doesn't explicitly contrast with all siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'query_loki_logs' or 'get_sift_analysis'. The description implies usage for error investigation but lacks explicit context, prerequisites, or exclusions.

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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